Upload 16 files
Browse filesupdate all mode weights
- model_collections/.DS_Store +0 -0
- model_collections/gemma/README.md +204 -0
- model_collections/gemma/adapter_config.json +28 -0
- model_collections/gemma/adapter_model.safetensors +3 -0
- model_collections/llamapro/README.md +204 -0
- model_collections/llamapro/adapter_config.json +28 -0
- model_collections/llamapro/adapter_model.safetensors +3 -0
- model_collections/mistral/README.md +204 -0
- model_collections/mistral/adapter_config.json +28 -0
- model_collections/mistral/adapter_model.safetensors +3 -0
- model_collections/protein_inference/.DS_Store +0 -0
- model_collections/protein_inference/adapter_config.json +31 -0
- model_collections/protein_inference/config.json +49 -0
- model_collections/spatial_inference/adapter_config.json +31 -0
- model_collections/spatial_inference/config.json +49 -0
- model_collections/spatial_inference/trainer_state.json +2610 -0
model_collections/.DS_Store
ADDED
Binary file (10.2 kB). View file
|
|
model_collections/gemma/README.md
ADDED
@@ -0,0 +1,204 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: peft
|
3 |
+
base_model: google/gemma-7b-it
|
4 |
+
---
|
5 |
+
|
6 |
+
# Model Card for Model ID
|
7 |
+
|
8 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
9 |
+
|
10 |
+
|
11 |
+
|
12 |
+
## Model Details
|
13 |
+
|
14 |
+
### Model Description
|
15 |
+
|
16 |
+
<!-- Provide a longer summary of what this model is. -->
|
17 |
+
|
18 |
+
|
19 |
+
|
20 |
+
- **Developed by:** [More Information Needed]
|
21 |
+
- **Funded by [optional]:** [More Information Needed]
|
22 |
+
- **Shared by [optional]:** [More Information Needed]
|
23 |
+
- **Model type:** [More Information Needed]
|
24 |
+
- **Language(s) (NLP):** [More Information Needed]
|
25 |
+
- **License:** [More Information Needed]
|
26 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
27 |
+
|
28 |
+
### Model Sources [optional]
|
29 |
+
|
30 |
+
<!-- Provide the basic links for the model. -->
|
31 |
+
|
32 |
+
- **Repository:** [More Information Needed]
|
33 |
+
- **Paper [optional]:** [More Information Needed]
|
34 |
+
- **Demo [optional]:** [More Information Needed]
|
35 |
+
|
36 |
+
## Uses
|
37 |
+
|
38 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
39 |
+
|
40 |
+
### Direct Use
|
41 |
+
|
42 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
43 |
+
|
44 |
+
[More Information Needed]
|
45 |
+
|
46 |
+
### Downstream Use [optional]
|
47 |
+
|
48 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
49 |
+
|
50 |
+
[More Information Needed]
|
51 |
+
|
52 |
+
### Out-of-Scope Use
|
53 |
+
|
54 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
55 |
+
|
56 |
+
[More Information Needed]
|
57 |
+
|
58 |
+
## Bias, Risks, and Limitations
|
59 |
+
|
60 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
61 |
+
|
62 |
+
[More Information Needed]
|
63 |
+
|
64 |
+
### Recommendations
|
65 |
+
|
66 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
67 |
+
|
68 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
69 |
+
|
70 |
+
## How to Get Started with the Model
|
71 |
+
|
72 |
+
Use the code below to get started with the model.
|
73 |
+
|
74 |
+
[More Information Needed]
|
75 |
+
|
76 |
+
## Training Details
|
77 |
+
|
78 |
+
### Training Data
|
79 |
+
|
80 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
81 |
+
|
82 |
+
[More Information Needed]
|
83 |
+
|
84 |
+
### Training Procedure
|
85 |
+
|
86 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
87 |
+
|
88 |
+
#### Preprocessing [optional]
|
89 |
+
|
90 |
+
[More Information Needed]
|
91 |
+
|
92 |
+
|
93 |
+
#### Training Hyperparameters
|
94 |
+
|
95 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
96 |
+
|
97 |
+
#### Speeds, Sizes, Times [optional]
|
98 |
+
|
99 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
100 |
+
|
101 |
+
[More Information Needed]
|
102 |
+
|
103 |
+
## Evaluation
|
104 |
+
|
105 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
106 |
+
|
107 |
+
### Testing Data, Factors & Metrics
|
108 |
+
|
109 |
+
#### Testing Data
|
110 |
+
|
111 |
+
<!-- This should link to a Dataset Card if possible. -->
|
112 |
+
|
113 |
+
[More Information Needed]
|
114 |
+
|
115 |
+
#### Factors
|
116 |
+
|
117 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
118 |
+
|
119 |
+
[More Information Needed]
|
120 |
+
|
121 |
+
#### Metrics
|
122 |
+
|
123 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
124 |
+
|
125 |
+
[More Information Needed]
|
126 |
+
|
127 |
+
### Results
|
128 |
+
|
129 |
+
[More Information Needed]
|
130 |
+
|
131 |
+
#### Summary
|
132 |
+
|
133 |
+
|
134 |
+
|
135 |
+
## Model Examination [optional]
|
136 |
+
|
137 |
+
<!-- Relevant interpretability work for the model goes here -->
|
138 |
+
|
139 |
+
[More Information Needed]
|
140 |
+
|
141 |
+
## Environmental Impact
|
142 |
+
|
143 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
144 |
+
|
145 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
146 |
+
|
147 |
+
- **Hardware Type:** [More Information Needed]
|
148 |
+
- **Hours used:** [More Information Needed]
|
149 |
+
- **Cloud Provider:** [More Information Needed]
|
150 |
+
- **Compute Region:** [More Information Needed]
|
151 |
+
- **Carbon Emitted:** [More Information Needed]
|
152 |
+
|
153 |
+
## Technical Specifications [optional]
|
154 |
+
|
155 |
+
### Model Architecture and Objective
|
156 |
+
|
157 |
+
[More Information Needed]
|
158 |
+
|
159 |
+
### Compute Infrastructure
|
160 |
+
|
161 |
+
[More Information Needed]
|
162 |
+
|
163 |
+
#### Hardware
|
164 |
+
|
165 |
+
[More Information Needed]
|
166 |
+
|
167 |
+
#### Software
|
168 |
+
|
169 |
+
[More Information Needed]
|
170 |
+
|
171 |
+
## Citation [optional]
|
172 |
+
|
173 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
174 |
+
|
175 |
+
**BibTeX:**
|
176 |
+
|
177 |
+
[More Information Needed]
|
178 |
+
|
179 |
+
**APA:**
|
180 |
+
|
181 |
+
[More Information Needed]
|
182 |
+
|
183 |
+
## Glossary [optional]
|
184 |
+
|
185 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
186 |
+
|
187 |
+
[More Information Needed]
|
188 |
+
|
189 |
+
## More Information [optional]
|
190 |
+
|
191 |
+
[More Information Needed]
|
192 |
+
|
193 |
+
## Model Card Authors [optional]
|
194 |
+
|
195 |
+
[More Information Needed]
|
196 |
+
|
197 |
+
## Model Card Contact
|
198 |
+
|
199 |
+
[More Information Needed]
|
200 |
+
|
201 |
+
|
202 |
+
### Framework versions
|
203 |
+
|
204 |
+
- PEFT 0.7.1
|
model_collections/gemma/adapter_config.json
ADDED
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"alpha_pattern": {},
|
3 |
+
"auto_mapping": null,
|
4 |
+
"base_model_name_or_path": "google/gemma-7b-it",
|
5 |
+
"bias": "none",
|
6 |
+
"fan_in_fan_out": false,
|
7 |
+
"inference_mode": true,
|
8 |
+
"init_lora_weights": true,
|
9 |
+
"layers_pattern": null,
|
10 |
+
"layers_to_transform": null,
|
11 |
+
"loftq_config": {},
|
12 |
+
"lora_alpha": 16,
|
13 |
+
"lora_dropout": 0.05,
|
14 |
+
"megatron_config": null,
|
15 |
+
"megatron_core": "megatron.core",
|
16 |
+
"modules_to_save": null,
|
17 |
+
"peft_type": "LORA",
|
18 |
+
"r": 8,
|
19 |
+
"rank_pattern": {},
|
20 |
+
"revision": null,
|
21 |
+
"target_modules": [
|
22 |
+
"q_proj",
|
23 |
+
"k_proj",
|
24 |
+
"o_proj",
|
25 |
+
"v_proj"
|
26 |
+
],
|
27 |
+
"task_type": "CAUSAL_LM"
|
28 |
+
}
|
model_collections/gemma/adapter_model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:cc7d3de01d46be5f9b9052a82d9792e7d5459d76c2725c2800728eaf3064f890
|
3 |
+
size 25719896
|
model_collections/llamapro/README.md
ADDED
@@ -0,0 +1,204 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: peft
|
3 |
+
base_model: TencentARC/LLaMA-Pro-8B
|
4 |
+
---
|
5 |
+
|
6 |
+
# Model Card for Model ID
|
7 |
+
|
8 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
9 |
+
|
10 |
+
|
11 |
+
|
12 |
+
## Model Details
|
13 |
+
|
14 |
+
### Model Description
|
15 |
+
|
16 |
+
<!-- Provide a longer summary of what this model is. -->
|
17 |
+
|
18 |
+
|
19 |
+
|
20 |
+
- **Developed by:** [More Information Needed]
|
21 |
+
- **Funded by [optional]:** [More Information Needed]
|
22 |
+
- **Shared by [optional]:** [More Information Needed]
|
23 |
+
- **Model type:** [More Information Needed]
|
24 |
+
- **Language(s) (NLP):** [More Information Needed]
|
25 |
+
- **License:** [More Information Needed]
|
26 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
27 |
+
|
28 |
+
### Model Sources [optional]
|
29 |
+
|
30 |
+
<!-- Provide the basic links for the model. -->
|
31 |
+
|
32 |
+
- **Repository:** [More Information Needed]
|
33 |
+
- **Paper [optional]:** [More Information Needed]
|
34 |
+
- **Demo [optional]:** [More Information Needed]
|
35 |
+
|
36 |
+
## Uses
|
37 |
+
|
38 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
39 |
+
|
40 |
+
### Direct Use
|
41 |
+
|
42 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
43 |
+
|
44 |
+
[More Information Needed]
|
45 |
+
|
46 |
+
### Downstream Use [optional]
|
47 |
+
|
48 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
49 |
+
|
50 |
+
[More Information Needed]
|
51 |
+
|
52 |
+
### Out-of-Scope Use
|
53 |
+
|
54 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
55 |
+
|
56 |
+
[More Information Needed]
|
57 |
+
|
58 |
+
## Bias, Risks, and Limitations
|
59 |
+
|
60 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
61 |
+
|
62 |
+
[More Information Needed]
|
63 |
+
|
64 |
+
### Recommendations
|
65 |
+
|
66 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
67 |
+
|
68 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
69 |
+
|
70 |
+
## How to Get Started with the Model
|
71 |
+
|
72 |
+
Use the code below to get started with the model.
|
73 |
+
|
74 |
+
[More Information Needed]
|
75 |
+
|
76 |
+
## Training Details
|
77 |
+
|
78 |
+
### Training Data
|
79 |
+
|
80 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
81 |
+
|
82 |
+
[More Information Needed]
|
83 |
+
|
84 |
+
### Training Procedure
|
85 |
+
|
86 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
87 |
+
|
88 |
+
#### Preprocessing [optional]
|
89 |
+
|
90 |
+
[More Information Needed]
|
91 |
+
|
92 |
+
|
93 |
+
#### Training Hyperparameters
|
94 |
+
|
95 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
96 |
+
|
97 |
+
#### Speeds, Sizes, Times [optional]
|
98 |
+
|
99 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
100 |
+
|
101 |
+
[More Information Needed]
|
102 |
+
|
103 |
+
## Evaluation
|
104 |
+
|
105 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
106 |
+
|
107 |
+
### Testing Data, Factors & Metrics
|
108 |
+
|
109 |
+
#### Testing Data
|
110 |
+
|
111 |
+
<!-- This should link to a Dataset Card if possible. -->
|
112 |
+
|
113 |
+
[More Information Needed]
|
114 |
+
|
115 |
+
#### Factors
|
116 |
+
|
117 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
118 |
+
|
119 |
+
[More Information Needed]
|
120 |
+
|
121 |
+
#### Metrics
|
122 |
+
|
123 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
124 |
+
|
125 |
+
[More Information Needed]
|
126 |
+
|
127 |
+
### Results
|
128 |
+
|
129 |
+
[More Information Needed]
|
130 |
+
|
131 |
+
#### Summary
|
132 |
+
|
133 |
+
|
134 |
+
|
135 |
+
## Model Examination [optional]
|
136 |
+
|
137 |
+
<!-- Relevant interpretability work for the model goes here -->
|
138 |
+
|
139 |
+
[More Information Needed]
|
140 |
+
|
141 |
+
## Environmental Impact
|
142 |
+
|
143 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
144 |
+
|
145 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
146 |
+
|
147 |
+
- **Hardware Type:** [More Information Needed]
|
148 |
+
- **Hours used:** [More Information Needed]
|
149 |
+
- **Cloud Provider:** [More Information Needed]
|
150 |
+
- **Compute Region:** [More Information Needed]
|
151 |
+
- **Carbon Emitted:** [More Information Needed]
|
152 |
+
|
153 |
+
## Technical Specifications [optional]
|
154 |
+
|
155 |
+
### Model Architecture and Objective
|
156 |
+
|
157 |
+
[More Information Needed]
|
158 |
+
|
159 |
+
### Compute Infrastructure
|
160 |
+
|
161 |
+
[More Information Needed]
|
162 |
+
|
163 |
+
#### Hardware
|
164 |
+
|
165 |
+
[More Information Needed]
|
166 |
+
|
167 |
+
#### Software
|
168 |
+
|
169 |
+
[More Information Needed]
|
170 |
+
|
171 |
+
## Citation [optional]
|
172 |
+
|
173 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
174 |
+
|
175 |
+
**BibTeX:**
|
176 |
+
|
177 |
+
[More Information Needed]
|
178 |
+
|
179 |
+
**APA:**
|
180 |
+
|
181 |
+
[More Information Needed]
|
182 |
+
|
183 |
+
## Glossary [optional]
|
184 |
+
|
185 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
186 |
+
|
187 |
+
[More Information Needed]
|
188 |
+
|
189 |
+
## More Information [optional]
|
190 |
+
|
191 |
+
[More Information Needed]
|
192 |
+
|
193 |
+
## Model Card Authors [optional]
|
194 |
+
|
195 |
+
[More Information Needed]
|
196 |
+
|
197 |
+
## Model Card Contact
|
198 |
+
|
199 |
+
[More Information Needed]
|
200 |
+
|
201 |
+
|
202 |
+
### Framework versions
|
203 |
+
|
204 |
+
- PEFT 0.7.1
|
model_collections/llamapro/adapter_config.json
ADDED
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"alpha_pattern": {},
|
3 |
+
"auto_mapping": null,
|
4 |
+
"base_model_name_or_path": "TencentARC/LLaMA-Pro-8B",
|
5 |
+
"bias": "none",
|
6 |
+
"fan_in_fan_out": false,
|
7 |
+
"inference_mode": true,
|
8 |
+
"init_lora_weights": true,
|
9 |
+
"layers_pattern": null,
|
10 |
+
"layers_to_transform": null,
|
11 |
+
"loftq_config": {},
|
12 |
+
"lora_alpha": 16,
|
13 |
+
"lora_dropout": 0.05,
|
14 |
+
"megatron_config": null,
|
15 |
+
"megatron_core": "megatron.core",
|
16 |
+
"modules_to_save": null,
|
17 |
+
"peft_type": "LORA",
|
18 |
+
"r": 8,
|
19 |
+
"rank_pattern": {},
|
20 |
+
"revision": null,
|
21 |
+
"target_modules": [
|
22 |
+
"k_proj",
|
23 |
+
"o_proj",
|
24 |
+
"q_proj",
|
25 |
+
"v_proj"
|
26 |
+
],
|
27 |
+
"task_type": "CAUSAL_LM"
|
28 |
+
}
|
model_collections/llamapro/adapter_model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:561a6d3d27f8a0703249728ad559ee7cb32ca684088629df47cfcdee5d050c9f
|
3 |
+
size 41985712
|
model_collections/mistral/README.md
ADDED
@@ -0,0 +1,204 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
library_name: peft
|
3 |
+
base_model: mistralai/Mistral-7B-Instruct-v0.2
|
4 |
+
---
|
5 |
+
|
6 |
+
# Model Card for Model ID
|
7 |
+
|
8 |
+
<!-- Provide a quick summary of what the model is/does. -->
|
9 |
+
|
10 |
+
|
11 |
+
|
12 |
+
## Model Details
|
13 |
+
|
14 |
+
### Model Description
|
15 |
+
|
16 |
+
<!-- Provide a longer summary of what this model is. -->
|
17 |
+
|
18 |
+
|
19 |
+
|
20 |
+
- **Developed by:** [More Information Needed]
|
21 |
+
- **Funded by [optional]:** [More Information Needed]
|
22 |
+
- **Shared by [optional]:** [More Information Needed]
|
23 |
+
- **Model type:** [More Information Needed]
|
24 |
+
- **Language(s) (NLP):** [More Information Needed]
|
25 |
+
- **License:** [More Information Needed]
|
26 |
+
- **Finetuned from model [optional]:** [More Information Needed]
|
27 |
+
|
28 |
+
### Model Sources [optional]
|
29 |
+
|
30 |
+
<!-- Provide the basic links for the model. -->
|
31 |
+
|
32 |
+
- **Repository:** [More Information Needed]
|
33 |
+
- **Paper [optional]:** [More Information Needed]
|
34 |
+
- **Demo [optional]:** [More Information Needed]
|
35 |
+
|
36 |
+
## Uses
|
37 |
+
|
38 |
+
<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
|
39 |
+
|
40 |
+
### Direct Use
|
41 |
+
|
42 |
+
<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
|
43 |
+
|
44 |
+
[More Information Needed]
|
45 |
+
|
46 |
+
### Downstream Use [optional]
|
47 |
+
|
48 |
+
<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
|
49 |
+
|
50 |
+
[More Information Needed]
|
51 |
+
|
52 |
+
### Out-of-Scope Use
|
53 |
+
|
54 |
+
<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
|
55 |
+
|
56 |
+
[More Information Needed]
|
57 |
+
|
58 |
+
## Bias, Risks, and Limitations
|
59 |
+
|
60 |
+
<!-- This section is meant to convey both technical and sociotechnical limitations. -->
|
61 |
+
|
62 |
+
[More Information Needed]
|
63 |
+
|
64 |
+
### Recommendations
|
65 |
+
|
66 |
+
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
|
67 |
+
|
68 |
+
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
|
69 |
+
|
70 |
+
## How to Get Started with the Model
|
71 |
+
|
72 |
+
Use the code below to get started with the model.
|
73 |
+
|
74 |
+
[More Information Needed]
|
75 |
+
|
76 |
+
## Training Details
|
77 |
+
|
78 |
+
### Training Data
|
79 |
+
|
80 |
+
<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
|
81 |
+
|
82 |
+
[More Information Needed]
|
83 |
+
|
84 |
+
### Training Procedure
|
85 |
+
|
86 |
+
<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
|
87 |
+
|
88 |
+
#### Preprocessing [optional]
|
89 |
+
|
90 |
+
[More Information Needed]
|
91 |
+
|
92 |
+
|
93 |
+
#### Training Hyperparameters
|
94 |
+
|
95 |
+
- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
|
96 |
+
|
97 |
+
#### Speeds, Sizes, Times [optional]
|
98 |
+
|
99 |
+
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
100 |
+
|
101 |
+
[More Information Needed]
|
102 |
+
|
103 |
+
## Evaluation
|
104 |
+
|
105 |
+
<!-- This section describes the evaluation protocols and provides the results. -->
|
106 |
+
|
107 |
+
### Testing Data, Factors & Metrics
|
108 |
+
|
109 |
+
#### Testing Data
|
110 |
+
|
111 |
+
<!-- This should link to a Dataset Card if possible. -->
|
112 |
+
|
113 |
+
[More Information Needed]
|
114 |
+
|
115 |
+
#### Factors
|
116 |
+
|
117 |
+
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
118 |
+
|
119 |
+
[More Information Needed]
|
120 |
+
|
121 |
+
#### Metrics
|
122 |
+
|
123 |
+
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
124 |
+
|
125 |
+
[More Information Needed]
|
126 |
+
|
127 |
+
### Results
|
128 |
+
|
129 |
+
[More Information Needed]
|
130 |
+
|
131 |
+
#### Summary
|
132 |
+
|
133 |
+
|
134 |
+
|
135 |
+
## Model Examination [optional]
|
136 |
+
|
137 |
+
<!-- Relevant interpretability work for the model goes here -->
|
138 |
+
|
139 |
+
[More Information Needed]
|
140 |
+
|
141 |
+
## Environmental Impact
|
142 |
+
|
143 |
+
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
144 |
+
|
145 |
+
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
146 |
+
|
147 |
+
- **Hardware Type:** [More Information Needed]
|
148 |
+
- **Hours used:** [More Information Needed]
|
149 |
+
- **Cloud Provider:** [More Information Needed]
|
150 |
+
- **Compute Region:** [More Information Needed]
|
151 |
+
- **Carbon Emitted:** [More Information Needed]
|
152 |
+
|
153 |
+
## Technical Specifications [optional]
|
154 |
+
|
155 |
+
### Model Architecture and Objective
|
156 |
+
|
157 |
+
[More Information Needed]
|
158 |
+
|
159 |
+
### Compute Infrastructure
|
160 |
+
|
161 |
+
[More Information Needed]
|
162 |
+
|
163 |
+
#### Hardware
|
164 |
+
|
165 |
+
[More Information Needed]
|
166 |
+
|
167 |
+
#### Software
|
168 |
+
|
169 |
+
[More Information Needed]
|
170 |
+
|
171 |
+
## Citation [optional]
|
172 |
+
|
173 |
+
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
174 |
+
|
175 |
+
**BibTeX:**
|
176 |
+
|
177 |
+
[More Information Needed]
|
178 |
+
|
179 |
+
**APA:**
|
180 |
+
|
181 |
+
[More Information Needed]
|
182 |
+
|
183 |
+
## Glossary [optional]
|
184 |
+
|
185 |
+
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
186 |
+
|
187 |
+
[More Information Needed]
|
188 |
+
|
189 |
+
## More Information [optional]
|
190 |
+
|
191 |
+
[More Information Needed]
|
192 |
+
|
193 |
+
## Model Card Authors [optional]
|
194 |
+
|
195 |
+
[More Information Needed]
|
196 |
+
|
197 |
+
## Model Card Contact
|
198 |
+
|
199 |
+
[More Information Needed]
|
200 |
+
|
201 |
+
|
202 |
+
### Framework versions
|
203 |
+
|
204 |
+
- PEFT 0.7.1
|
model_collections/mistral/adapter_config.json
ADDED
@@ -0,0 +1,28 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"alpha_pattern": {},
|
3 |
+
"auto_mapping": null,
|
4 |
+
"base_model_name_or_path": "mistralai/Mistral-7B-Instruct-v0.2",
|
5 |
+
"bias": "none",
|
6 |
+
"fan_in_fan_out": false,
|
7 |
+
"inference_mode": true,
|
8 |
+
"init_lora_weights": true,
|
9 |
+
"layers_pattern": null,
|
10 |
+
"layers_to_transform": null,
|
11 |
+
"loftq_config": {},
|
12 |
+
"lora_alpha": 16,
|
13 |
+
"lora_dropout": 0.05,
|
14 |
+
"megatron_config": null,
|
15 |
+
"megatron_core": "megatron.core",
|
16 |
+
"modules_to_save": null,
|
17 |
+
"peft_type": "LORA",
|
18 |
+
"r": 8,
|
19 |
+
"rank_pattern": {},
|
20 |
+
"revision": null,
|
21 |
+
"target_modules": [
|
22 |
+
"o_proj",
|
23 |
+
"k_proj",
|
24 |
+
"q_proj",
|
25 |
+
"v_proj"
|
26 |
+
],
|
27 |
+
"task_type": "CAUSAL_LM"
|
28 |
+
}
|
model_collections/mistral/adapter_model.safetensors
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:92f87345261ffb43f17bb23c3fc241d44b03d0c5de67da62cdd69deb241c78a1
|
3 |
+
size 27297032
|
model_collections/protein_inference/.DS_Store
ADDED
Binary file (6.15 kB). View file
|
|
model_collections/protein_inference/adapter_config.json
ADDED
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"alpha_pattern": {},
|
3 |
+
"auto_mapping": null,
|
4 |
+
"base_model_name_or_path": "./temp/llava-v1.5-7b",
|
5 |
+
"bias": "none",
|
6 |
+
"fan_in_fan_out": false,
|
7 |
+
"inference_mode": true,
|
8 |
+
"init_lora_weights": true,
|
9 |
+
"layers_pattern": null,
|
10 |
+
"layers_to_transform": null,
|
11 |
+
"loftq_config": {},
|
12 |
+
"lora_alpha": 256,
|
13 |
+
"lora_dropout": 0.05,
|
14 |
+
"megatron_config": null,
|
15 |
+
"megatron_core": "megatron.core",
|
16 |
+
"modules_to_save": null,
|
17 |
+
"peft_type": "LORA",
|
18 |
+
"r": 128,
|
19 |
+
"rank_pattern": {},
|
20 |
+
"revision": null,
|
21 |
+
"target_modules": [
|
22 |
+
"k_proj",
|
23 |
+
"gate_proj",
|
24 |
+
"q_proj",
|
25 |
+
"o_proj",
|
26 |
+
"up_proj",
|
27 |
+
"down_proj",
|
28 |
+
"v_proj"
|
29 |
+
],
|
30 |
+
"task_type": "CAUSAL_LM"
|
31 |
+
}
|
model_collections/protein_inference/config.json
ADDED
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "./temp/llava-v1.5-7b",
|
3 |
+
"architectures": [
|
4 |
+
"LlavaLlamaForCausalLM"
|
5 |
+
],
|
6 |
+
"attention_bias": false,
|
7 |
+
"attention_dropout": 0.0,
|
8 |
+
"bos_token_id": 1,
|
9 |
+
"eos_token_id": 2,
|
10 |
+
"freeze_mm_mlp_adapter": false,
|
11 |
+
"freeze_mm_vision_resampler": false,
|
12 |
+
"hidden_act": "silu",
|
13 |
+
"hidden_size": 4096,
|
14 |
+
"image_aspect_ratio": "pad",
|
15 |
+
"initializer_range": 0.02,
|
16 |
+
"intermediate_size": 11008,
|
17 |
+
"max_length": 4096,
|
18 |
+
"max_position_embeddings": 4096,
|
19 |
+
"mm_hidden_size": 1024,
|
20 |
+
"mm_patch_merge_type": "flat",
|
21 |
+
"mm_projector_lr": 2e-05,
|
22 |
+
"mm_projector_type": "mlp2x_gelu",
|
23 |
+
"mm_resampler_type": null,
|
24 |
+
"mm_use_im_patch_token": false,
|
25 |
+
"mm_use_im_start_end": false,
|
26 |
+
"mm_vision_select_feature": "patch",
|
27 |
+
"mm_vision_select_layer": -2,
|
28 |
+
"mm_vision_tower": "openai/clip-vit-large-patch14-336",
|
29 |
+
"model_type": "llava_llama",
|
30 |
+
"num_attention_heads": 32,
|
31 |
+
"num_hidden_layers": 32,
|
32 |
+
"num_key_value_heads": 32,
|
33 |
+
"pad_token_id": 0,
|
34 |
+
"pretraining_tp": 1,
|
35 |
+
"rms_norm_eps": 1e-05,
|
36 |
+
"rope_scaling": null,
|
37 |
+
"rope_theta": 10000.0,
|
38 |
+
"tie_word_embeddings": false,
|
39 |
+
"tokenizer_model_max_length": 512,
|
40 |
+
"tokenizer_padding_side": "right",
|
41 |
+
"torch_dtype": "float16",
|
42 |
+
"transformers_version": "4.37.2",
|
43 |
+
"tune_mm_mlp_adapter": false,
|
44 |
+
"tune_mm_vision_resampler": false,
|
45 |
+
"unfreeze_mm_vision_tower": false,
|
46 |
+
"use_cache": true,
|
47 |
+
"use_mm_proj": true,
|
48 |
+
"vocab_size": 32000
|
49 |
+
}
|
model_collections/spatial_inference/adapter_config.json
ADDED
@@ -0,0 +1,31 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"alpha_pattern": {},
|
3 |
+
"auto_mapping": null,
|
4 |
+
"base_model_name_or_path": "./temp/llava-v1.5-7b",
|
5 |
+
"bias": "none",
|
6 |
+
"fan_in_fan_out": false,
|
7 |
+
"inference_mode": true,
|
8 |
+
"init_lora_weights": true,
|
9 |
+
"layers_pattern": null,
|
10 |
+
"layers_to_transform": null,
|
11 |
+
"loftq_config": {},
|
12 |
+
"lora_alpha": 256,
|
13 |
+
"lora_dropout": 0.05,
|
14 |
+
"megatron_config": null,
|
15 |
+
"megatron_core": "megatron.core",
|
16 |
+
"modules_to_save": null,
|
17 |
+
"peft_type": "LORA",
|
18 |
+
"r": 128,
|
19 |
+
"rank_pattern": {},
|
20 |
+
"revision": null,
|
21 |
+
"target_modules": [
|
22 |
+
"k_proj",
|
23 |
+
"gate_proj",
|
24 |
+
"down_proj",
|
25 |
+
"o_proj",
|
26 |
+
"up_proj",
|
27 |
+
"q_proj",
|
28 |
+
"v_proj"
|
29 |
+
],
|
30 |
+
"task_type": "CAUSAL_LM"
|
31 |
+
}
|
model_collections/spatial_inference/config.json
ADDED
@@ -0,0 +1,49 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"_name_or_path": "./temp/llava-v1.5-7b",
|
3 |
+
"architectures": [
|
4 |
+
"LlavaLlamaForCausalLM"
|
5 |
+
],
|
6 |
+
"attention_bias": false,
|
7 |
+
"attention_dropout": 0.0,
|
8 |
+
"bos_token_id": 1,
|
9 |
+
"eos_token_id": 2,
|
10 |
+
"freeze_mm_mlp_adapter": false,
|
11 |
+
"freeze_mm_vision_resampler": false,
|
12 |
+
"hidden_act": "silu",
|
13 |
+
"hidden_size": 4096,
|
14 |
+
"image_aspect_ratio": "pad",
|
15 |
+
"initializer_range": 0.02,
|
16 |
+
"intermediate_size": 11008,
|
17 |
+
"max_length": 4096,
|
18 |
+
"max_position_embeddings": 4096,
|
19 |
+
"mm_hidden_size": 1024,
|
20 |
+
"mm_patch_merge_type": "flat",
|
21 |
+
"mm_projector_lr": 2e-05,
|
22 |
+
"mm_projector_type": "mlp2x_gelu",
|
23 |
+
"mm_resampler_type": null,
|
24 |
+
"mm_use_im_patch_token": false,
|
25 |
+
"mm_use_im_start_end": false,
|
26 |
+
"mm_vision_select_feature": "patch",
|
27 |
+
"mm_vision_select_layer": -2,
|
28 |
+
"mm_vision_tower": "openai/clip-vit-large-patch14-336",
|
29 |
+
"model_type": "llava_llama",
|
30 |
+
"num_attention_heads": 32,
|
31 |
+
"num_hidden_layers": 32,
|
32 |
+
"num_key_value_heads": 32,
|
33 |
+
"pad_token_id": 0,
|
34 |
+
"pretraining_tp": 1,
|
35 |
+
"rms_norm_eps": 1e-05,
|
36 |
+
"rope_scaling": null,
|
37 |
+
"rope_theta": 10000.0,
|
38 |
+
"tie_word_embeddings": false,
|
39 |
+
"tokenizer_model_max_length": 1024,
|
40 |
+
"tokenizer_padding_side": "right",
|
41 |
+
"torch_dtype": "float16",
|
42 |
+
"transformers_version": "4.37.2",
|
43 |
+
"tune_mm_mlp_adapter": false,
|
44 |
+
"tune_mm_vision_resampler": false,
|
45 |
+
"unfreeze_mm_vision_tower": false,
|
46 |
+
"use_cache": true,
|
47 |
+
"use_mm_proj": true,
|
48 |
+
"vocab_size": 32000
|
49 |
+
}
|
model_collections/spatial_inference/trainer_state.json
ADDED
@@ -0,0 +1,2610 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
{
|
2 |
+
"best_metric": null,
|
3 |
+
"best_model_checkpoint": null,
|
4 |
+
"epoch": 9.82857142857143,
|
5 |
+
"eval_steps": 500,
|
6 |
+
"global_step": 430,
|
7 |
+
"is_hyper_param_search": false,
|
8 |
+
"is_local_process_zero": true,
|
9 |
+
"is_world_process_zero": true,
|
10 |
+
"log_history": [
|
11 |
+
{
|
12 |
+
"epoch": 0.02,
|
13 |
+
"learning_rate": 1.5384615384615387e-05,
|
14 |
+
"loss": 5.1473,
|
15 |
+
"step": 1
|
16 |
+
},
|
17 |
+
{
|
18 |
+
"epoch": 0.05,
|
19 |
+
"learning_rate": 3.0769230769230774e-05,
|
20 |
+
"loss": 5.1654,
|
21 |
+
"step": 2
|
22 |
+
},
|
23 |
+
{
|
24 |
+
"epoch": 0.07,
|
25 |
+
"learning_rate": 4.615384615384616e-05,
|
26 |
+
"loss": 4.4404,
|
27 |
+
"step": 3
|
28 |
+
},
|
29 |
+
{
|
30 |
+
"epoch": 0.09,
|
31 |
+
"learning_rate": 6.153846153846155e-05,
|
32 |
+
"loss": 2.1218,
|
33 |
+
"step": 4
|
34 |
+
},
|
35 |
+
{
|
36 |
+
"epoch": 0.11,
|
37 |
+
"learning_rate": 7.692307692307693e-05,
|
38 |
+
"loss": 0.7891,
|
39 |
+
"step": 5
|
40 |
+
},
|
41 |
+
{
|
42 |
+
"epoch": 0.14,
|
43 |
+
"learning_rate": 9.230769230769232e-05,
|
44 |
+
"loss": 0.4084,
|
45 |
+
"step": 6
|
46 |
+
},
|
47 |
+
{
|
48 |
+
"epoch": 0.16,
|
49 |
+
"learning_rate": 0.0001076923076923077,
|
50 |
+
"loss": 0.2285,
|
51 |
+
"step": 7
|
52 |
+
},
|
53 |
+
{
|
54 |
+
"epoch": 0.18,
|
55 |
+
"learning_rate": 0.0001230769230769231,
|
56 |
+
"loss": 0.2082,
|
57 |
+
"step": 8
|
58 |
+
},
|
59 |
+
{
|
60 |
+
"epoch": 0.21,
|
61 |
+
"learning_rate": 0.00013846153846153847,
|
62 |
+
"loss": 0.1934,
|
63 |
+
"step": 9
|
64 |
+
},
|
65 |
+
{
|
66 |
+
"epoch": 0.23,
|
67 |
+
"learning_rate": 0.00015384615384615385,
|
68 |
+
"loss": 0.1951,
|
69 |
+
"step": 10
|
70 |
+
},
|
71 |
+
{
|
72 |
+
"epoch": 0.25,
|
73 |
+
"learning_rate": 0.00016923076923076923,
|
74 |
+
"loss": 0.1867,
|
75 |
+
"step": 11
|
76 |
+
},
|
77 |
+
{
|
78 |
+
"epoch": 0.27,
|
79 |
+
"learning_rate": 0.00018461538461538463,
|
80 |
+
"loss": 0.1931,
|
81 |
+
"step": 12
|
82 |
+
},
|
83 |
+
{
|
84 |
+
"epoch": 0.3,
|
85 |
+
"learning_rate": 0.0002,
|
86 |
+
"loss": 0.1895,
|
87 |
+
"step": 13
|
88 |
+
},
|
89 |
+
{
|
90 |
+
"epoch": 0.32,
|
91 |
+
"learning_rate": 0.00019999716210981734,
|
92 |
+
"loss": 0.16,
|
93 |
+
"step": 14
|
94 |
+
},
|
95 |
+
{
|
96 |
+
"epoch": 0.34,
|
97 |
+
"learning_rate": 0.00019998864860034169,
|
98 |
+
"loss": 0.2126,
|
99 |
+
"step": 15
|
100 |
+
},
|
101 |
+
{
|
102 |
+
"epoch": 0.37,
|
103 |
+
"learning_rate": 0.0001999744599547812,
|
104 |
+
"loss": 0.1772,
|
105 |
+
"step": 16
|
106 |
+
},
|
107 |
+
{
|
108 |
+
"epoch": 0.39,
|
109 |
+
"learning_rate": 0.0001999545969784522,
|
110 |
+
"loss": 0.1949,
|
111 |
+
"step": 17
|
112 |
+
},
|
113 |
+
{
|
114 |
+
"epoch": 0.41,
|
115 |
+
"learning_rate": 0.00019992906079873365,
|
116 |
+
"loss": 0.1923,
|
117 |
+
"step": 18
|
118 |
+
},
|
119 |
+
{
|
120 |
+
"epoch": 0.43,
|
121 |
+
"learning_rate": 0.00019989785286500295,
|
122 |
+
"loss": 0.1709,
|
123 |
+
"step": 19
|
124 |
+
},
|
125 |
+
{
|
126 |
+
"epoch": 0.46,
|
127 |
+
"learning_rate": 0.0001998609749485539,
|
128 |
+
"loss": 0.1823,
|
129 |
+
"step": 20
|
130 |
+
},
|
131 |
+
{
|
132 |
+
"epoch": 0.48,
|
133 |
+
"learning_rate": 0.0001998184291424961,
|
134 |
+
"loss": 0.1656,
|
135 |
+
"step": 21
|
136 |
+
},
|
137 |
+
{
|
138 |
+
"epoch": 0.5,
|
139 |
+
"learning_rate": 0.00019977021786163598,
|
140 |
+
"loss": 0.194,
|
141 |
+
"step": 22
|
142 |
+
},
|
143 |
+
{
|
144 |
+
"epoch": 0.53,
|
145 |
+
"learning_rate": 0.00019971634384234003,
|
146 |
+
"loss": 0.174,
|
147 |
+
"step": 23
|
148 |
+
},
|
149 |
+
{
|
150 |
+
"epoch": 0.55,
|
151 |
+
"learning_rate": 0.00019965681014237917,
|
152 |
+
"loss": 0.1699,
|
153 |
+
"step": 24
|
154 |
+
},
|
155 |
+
{
|
156 |
+
"epoch": 0.57,
|
157 |
+
"learning_rate": 0.00019959162014075553,
|
158 |
+
"loss": 0.1771,
|
159 |
+
"step": 25
|
160 |
+
},
|
161 |
+
{
|
162 |
+
"epoch": 0.59,
|
163 |
+
"learning_rate": 0.00019952077753751036,
|
164 |
+
"loss": 0.1942,
|
165 |
+
"step": 26
|
166 |
+
},
|
167 |
+
{
|
168 |
+
"epoch": 0.62,
|
169 |
+
"learning_rate": 0.00019944428635351426,
|
170 |
+
"loss": 0.1818,
|
171 |
+
"step": 27
|
172 |
+
},
|
173 |
+
{
|
174 |
+
"epoch": 0.64,
|
175 |
+
"learning_rate": 0.00019936215093023884,
|
176 |
+
"loss": 0.1956,
|
177 |
+
"step": 28
|
178 |
+
},
|
179 |
+
{
|
180 |
+
"epoch": 0.66,
|
181 |
+
"learning_rate": 0.0001992743759295103,
|
182 |
+
"loss": 0.1738,
|
183 |
+
"step": 29
|
184 |
+
},
|
185 |
+
{
|
186 |
+
"epoch": 0.69,
|
187 |
+
"learning_rate": 0.00019918096633324492,
|
188 |
+
"loss": 0.1897,
|
189 |
+
"step": 30
|
190 |
+
},
|
191 |
+
{
|
192 |
+
"epoch": 0.71,
|
193 |
+
"learning_rate": 0.0001990819274431662,
|
194 |
+
"loss": 0.1558,
|
195 |
+
"step": 31
|
196 |
+
},
|
197 |
+
{
|
198 |
+
"epoch": 0.73,
|
199 |
+
"learning_rate": 0.00019897726488050406,
|
200 |
+
"loss": 0.2183,
|
201 |
+
"step": 32
|
202 |
+
},
|
203 |
+
{
|
204 |
+
"epoch": 0.75,
|
205 |
+
"learning_rate": 0.00019886698458567562,
|
206 |
+
"loss": 0.1844,
|
207 |
+
"step": 33
|
208 |
+
},
|
209 |
+
{
|
210 |
+
"epoch": 0.78,
|
211 |
+
"learning_rate": 0.00019875109281794825,
|
212 |
+
"loss": 0.1774,
|
213 |
+
"step": 34
|
214 |
+
},
|
215 |
+
{
|
216 |
+
"epoch": 0.8,
|
217 |
+
"learning_rate": 0.00019862959615508417,
|
218 |
+
"loss": 0.1709,
|
219 |
+
"step": 35
|
220 |
+
},
|
221 |
+
{
|
222 |
+
"epoch": 0.82,
|
223 |
+
"learning_rate": 0.00019850250149296703,
|
224 |
+
"loss": 0.2023,
|
225 |
+
"step": 36
|
226 |
+
},
|
227 |
+
{
|
228 |
+
"epoch": 0.85,
|
229 |
+
"learning_rate": 0.00019836981604521076,
|
230 |
+
"loss": 0.1717,
|
231 |
+
"step": 37
|
232 |
+
},
|
233 |
+
{
|
234 |
+
"epoch": 0.87,
|
235 |
+
"learning_rate": 0.00019823154734274997,
|
236 |
+
"loss": 0.1751,
|
237 |
+
"step": 38
|
238 |
+
},
|
239 |
+
{
|
240 |
+
"epoch": 0.89,
|
241 |
+
"learning_rate": 0.0001980877032334125,
|
242 |
+
"loss": 0.1903,
|
243 |
+
"step": 39
|
244 |
+
},
|
245 |
+
{
|
246 |
+
"epoch": 0.91,
|
247 |
+
"learning_rate": 0.00019793829188147406,
|
248 |
+
"loss": 0.2017,
|
249 |
+
"step": 40
|
250 |
+
},
|
251 |
+
{
|
252 |
+
"epoch": 0.94,
|
253 |
+
"learning_rate": 0.00019778332176719483,
|
254 |
+
"loss": 0.1651,
|
255 |
+
"step": 41
|
256 |
+
},
|
257 |
+
{
|
258 |
+
"epoch": 0.96,
|
259 |
+
"learning_rate": 0.00019762280168633814,
|
260 |
+
"loss": 0.1913,
|
261 |
+
"step": 42
|
262 |
+
},
|
263 |
+
{
|
264 |
+
"epoch": 0.98,
|
265 |
+
"learning_rate": 0.0001974567407496712,
|
266 |
+
"loss": 0.1749,
|
267 |
+
"step": 43
|
268 |
+
},
|
269 |
+
{
|
270 |
+
"epoch": 1.01,
|
271 |
+
"learning_rate": 0.0001972851483824481,
|
272 |
+
"loss": 0.1953,
|
273 |
+
"step": 44
|
274 |
+
},
|
275 |
+
{
|
276 |
+
"epoch": 1.03,
|
277 |
+
"learning_rate": 0.00019710803432387465,
|
278 |
+
"loss": 0.2126,
|
279 |
+
"step": 45
|
280 |
+
},
|
281 |
+
{
|
282 |
+
"epoch": 1.05,
|
283 |
+
"learning_rate": 0.00019692540862655585,
|
284 |
+
"loss": 0.181,
|
285 |
+
"step": 46
|
286 |
+
},
|
287 |
+
{
|
288 |
+
"epoch": 1.07,
|
289 |
+
"learning_rate": 0.0001967372816559252,
|
290 |
+
"loss": 0.176,
|
291 |
+
"step": 47
|
292 |
+
},
|
293 |
+
{
|
294 |
+
"epoch": 1.1,
|
295 |
+
"learning_rate": 0.00019654366408965635,
|
296 |
+
"loss": 0.1655,
|
297 |
+
"step": 48
|
298 |
+
},
|
299 |
+
{
|
300 |
+
"epoch": 1.12,
|
301 |
+
"learning_rate": 0.00019634456691705702,
|
302 |
+
"loss": 0.1676,
|
303 |
+
"step": 49
|
304 |
+
},
|
305 |
+
{
|
306 |
+
"epoch": 1.14,
|
307 |
+
"learning_rate": 0.00019614000143844558,
|
308 |
+
"loss": 0.1438,
|
309 |
+
"step": 50
|
310 |
+
},
|
311 |
+
{
|
312 |
+
"epoch": 1.17,
|
313 |
+
"learning_rate": 0.0001959299792645092,
|
314 |
+
"loss": 0.1915,
|
315 |
+
"step": 51
|
316 |
+
},
|
317 |
+
{
|
318 |
+
"epoch": 1.19,
|
319 |
+
"learning_rate": 0.00019571451231564525,
|
320 |
+
"loss": 0.2314,
|
321 |
+
"step": 52
|
322 |
+
},
|
323 |
+
{
|
324 |
+
"epoch": 1.21,
|
325 |
+
"learning_rate": 0.00019549361282128445,
|
326 |
+
"loss": 0.1736,
|
327 |
+
"step": 53
|
328 |
+
},
|
329 |
+
{
|
330 |
+
"epoch": 1.23,
|
331 |
+
"learning_rate": 0.00019526729331919697,
|
332 |
+
"loss": 0.1765,
|
333 |
+
"step": 54
|
334 |
+
},
|
335 |
+
{
|
336 |
+
"epoch": 1.26,
|
337 |
+
"learning_rate": 0.00019503556665478067,
|
338 |
+
"loss": 0.1969,
|
339 |
+
"step": 55
|
340 |
+
},
|
341 |
+
{
|
342 |
+
"epoch": 1.28,
|
343 |
+
"learning_rate": 0.00019479844598033202,
|
344 |
+
"loss": 0.1968,
|
345 |
+
"step": 56
|
346 |
+
},
|
347 |
+
{
|
348 |
+
"epoch": 1.3,
|
349 |
+
"learning_rate": 0.0001945559447542998,
|
350 |
+
"loss": 0.1724,
|
351 |
+
"step": 57
|
352 |
+
},
|
353 |
+
{
|
354 |
+
"epoch": 1.33,
|
355 |
+
"learning_rate": 0.00019430807674052092,
|
356 |
+
"loss": 0.2096,
|
357 |
+
"step": 58
|
358 |
+
},
|
359 |
+
{
|
360 |
+
"epoch": 1.35,
|
361 |
+
"learning_rate": 0.00019405485600743942,
|
362 |
+
"loss": 0.1861,
|
363 |
+
"step": 59
|
364 |
+
},
|
365 |
+
{
|
366 |
+
"epoch": 1.37,
|
367 |
+
"learning_rate": 0.00019379629692730798,
|
368 |
+
"loss": 0.1752,
|
369 |
+
"step": 60
|
370 |
+
},
|
371 |
+
{
|
372 |
+
"epoch": 1.39,
|
373 |
+
"learning_rate": 0.00019353241417537214,
|
374 |
+
"loss": 0.1746,
|
375 |
+
"step": 61
|
376 |
+
},
|
377 |
+
{
|
378 |
+
"epoch": 1.42,
|
379 |
+
"learning_rate": 0.00019326322272903722,
|
380 |
+
"loss": 0.175,
|
381 |
+
"step": 62
|
382 |
+
},
|
383 |
+
{
|
384 |
+
"epoch": 1.44,
|
385 |
+
"learning_rate": 0.00019298873786701857,
|
386 |
+
"loss": 0.1752,
|
387 |
+
"step": 63
|
388 |
+
},
|
389 |
+
{
|
390 |
+
"epoch": 1.46,
|
391 |
+
"learning_rate": 0.00019270897516847403,
|
392 |
+
"loss": 0.1719,
|
393 |
+
"step": 64
|
394 |
+
},
|
395 |
+
{
|
396 |
+
"epoch": 1.49,
|
397 |
+
"learning_rate": 0.00019242395051212,
|
398 |
+
"loss": 0.1814,
|
399 |
+
"step": 65
|
400 |
+
},
|
401 |
+
{
|
402 |
+
"epoch": 1.51,
|
403 |
+
"learning_rate": 0.00019213368007532986,
|
404 |
+
"loss": 0.1792,
|
405 |
+
"step": 66
|
406 |
+
},
|
407 |
+
{
|
408 |
+
"epoch": 1.53,
|
409 |
+
"learning_rate": 0.00019183818033321614,
|
410 |
+
"loss": 0.1683,
|
411 |
+
"step": 67
|
412 |
+
},
|
413 |
+
{
|
414 |
+
"epoch": 1.55,
|
415 |
+
"learning_rate": 0.00019153746805769512,
|
416 |
+
"loss": 0.175,
|
417 |
+
"step": 68
|
418 |
+
},
|
419 |
+
{
|
420 |
+
"epoch": 1.58,
|
421 |
+
"learning_rate": 0.00019123156031653515,
|
422 |
+
"loss": 0.1558,
|
423 |
+
"step": 69
|
424 |
+
},
|
425 |
+
{
|
426 |
+
"epoch": 1.6,
|
427 |
+
"learning_rate": 0.00019092047447238773,
|
428 |
+
"loss": 0.1907,
|
429 |
+
"step": 70
|
430 |
+
},
|
431 |
+
{
|
432 |
+
"epoch": 1.62,
|
433 |
+
"learning_rate": 0.00019060422818180207,
|
434 |
+
"loss": 0.2572,
|
435 |
+
"step": 71
|
436 |
+
},
|
437 |
+
{
|
438 |
+
"epoch": 1.65,
|
439 |
+
"learning_rate": 0.00019028283939422308,
|
440 |
+
"loss": 0.1781,
|
441 |
+
"step": 72
|
442 |
+
},
|
443 |
+
{
|
444 |
+
"epoch": 1.67,
|
445 |
+
"learning_rate": 0.0001899563263509725,
|
446 |
+
"loss": 0.1659,
|
447 |
+
"step": 73
|
448 |
+
},
|
449 |
+
{
|
450 |
+
"epoch": 1.69,
|
451 |
+
"learning_rate": 0.00018962470758421342,
|
452 |
+
"loss": 0.174,
|
453 |
+
"step": 74
|
454 |
+
},
|
455 |
+
{
|
456 |
+
"epoch": 1.71,
|
457 |
+
"learning_rate": 0.0001892880019158988,
|
458 |
+
"loss": 0.1795,
|
459 |
+
"step": 75
|
460 |
+
},
|
461 |
+
{
|
462 |
+
"epoch": 1.74,
|
463 |
+
"learning_rate": 0.00018894622845670283,
|
464 |
+
"loss": 0.1712,
|
465 |
+
"step": 76
|
466 |
+
},
|
467 |
+
{
|
468 |
+
"epoch": 1.76,
|
469 |
+
"learning_rate": 0.00018859940660493634,
|
470 |
+
"loss": 0.1628,
|
471 |
+
"step": 77
|
472 |
+
},
|
473 |
+
{
|
474 |
+
"epoch": 1.78,
|
475 |
+
"learning_rate": 0.00018824755604544594,
|
476 |
+
"loss": 0.1901,
|
477 |
+
"step": 78
|
478 |
+
},
|
479 |
+
{
|
480 |
+
"epoch": 1.81,
|
481 |
+
"learning_rate": 0.0001878906967484966,
|
482 |
+
"loss": 0.1549,
|
483 |
+
"step": 79
|
484 |
+
},
|
485 |
+
{
|
486 |
+
"epoch": 1.83,
|
487 |
+
"learning_rate": 0.0001875288489686382,
|
488 |
+
"loss": 0.1972,
|
489 |
+
"step": 80
|
490 |
+
},
|
491 |
+
{
|
492 |
+
"epoch": 1.85,
|
493 |
+
"learning_rate": 0.00018716203324355607,
|
494 |
+
"loss": 0.1758,
|
495 |
+
"step": 81
|
496 |
+
},
|
497 |
+
{
|
498 |
+
"epoch": 1.87,
|
499 |
+
"learning_rate": 0.00018679027039290497,
|
500 |
+
"loss": 0.1772,
|
501 |
+
"step": 82
|
502 |
+
},
|
503 |
+
{
|
504 |
+
"epoch": 1.9,
|
505 |
+
"learning_rate": 0.0001864135815171279,
|
506 |
+
"loss": 0.1839,
|
507 |
+
"step": 83
|
508 |
+
},
|
509 |
+
{
|
510 |
+
"epoch": 1.92,
|
511 |
+
"learning_rate": 0.00018603198799625807,
|
512 |
+
"loss": 0.192,
|
513 |
+
"step": 84
|
514 |
+
},
|
515 |
+
{
|
516 |
+
"epoch": 1.94,
|
517 |
+
"learning_rate": 0.00018564551148870563,
|
518 |
+
"loss": 0.1795,
|
519 |
+
"step": 85
|
520 |
+
},
|
521 |
+
{
|
522 |
+
"epoch": 1.97,
|
523 |
+
"learning_rate": 0.00018525417393002824,
|
524 |
+
"loss": 0.1731,
|
525 |
+
"step": 86
|
526 |
+
},
|
527 |
+
{
|
528 |
+
"epoch": 1.99,
|
529 |
+
"learning_rate": 0.00018485799753168634,
|
530 |
+
"loss": 0.1965,
|
531 |
+
"step": 87
|
532 |
+
},
|
533 |
+
{
|
534 |
+
"epoch": 2.01,
|
535 |
+
"learning_rate": 0.00018445700477978205,
|
536 |
+
"loss": 0.214,
|
537 |
+
"step": 88
|
538 |
+
},
|
539 |
+
{
|
540 |
+
"epoch": 2.03,
|
541 |
+
"learning_rate": 0.0001840512184337833,
|
542 |
+
"loss": 0.2024,
|
543 |
+
"step": 89
|
544 |
+
},
|
545 |
+
{
|
546 |
+
"epoch": 2.06,
|
547 |
+
"learning_rate": 0.00018364066152523183,
|
548 |
+
"loss": 0.1786,
|
549 |
+
"step": 90
|
550 |
+
},
|
551 |
+
{
|
552 |
+
"epoch": 2.08,
|
553 |
+
"learning_rate": 0.00018322535735643605,
|
554 |
+
"loss": 0.1938,
|
555 |
+
"step": 91
|
556 |
+
},
|
557 |
+
{
|
558 |
+
"epoch": 2.1,
|
559 |
+
"learning_rate": 0.00018280532949914842,
|
560 |
+
"loss": 0.1634,
|
561 |
+
"step": 92
|
562 |
+
},
|
563 |
+
{
|
564 |
+
"epoch": 2.13,
|
565 |
+
"learning_rate": 0.0001823806017932276,
|
566 |
+
"loss": 0.1655,
|
567 |
+
"step": 93
|
568 |
+
},
|
569 |
+
{
|
570 |
+
"epoch": 2.15,
|
571 |
+
"learning_rate": 0.00018195119834528534,
|
572 |
+
"loss": 0.1635,
|
573 |
+
"step": 94
|
574 |
+
},
|
575 |
+
{
|
576 |
+
"epoch": 2.17,
|
577 |
+
"learning_rate": 0.00018151714352731822,
|
578 |
+
"loss": 0.1938,
|
579 |
+
"step": 95
|
580 |
+
},
|
581 |
+
{
|
582 |
+
"epoch": 2.19,
|
583 |
+
"learning_rate": 0.00018107846197532433,
|
584 |
+
"loss": 0.1696,
|
585 |
+
"step": 96
|
586 |
+
},
|
587 |
+
{
|
588 |
+
"epoch": 2.22,
|
589 |
+
"learning_rate": 0.00018063517858790516,
|
590 |
+
"loss": 0.1806,
|
591 |
+
"step": 97
|
592 |
+
},
|
593 |
+
{
|
594 |
+
"epoch": 2.24,
|
595 |
+
"learning_rate": 0.00018018731852485206,
|
596 |
+
"loss": 0.1826,
|
597 |
+
"step": 98
|
598 |
+
},
|
599 |
+
{
|
600 |
+
"epoch": 2.26,
|
601 |
+
"learning_rate": 0.00017973490720571864,
|
602 |
+
"loss": 0.1976,
|
603 |
+
"step": 99
|
604 |
+
},
|
605 |
+
{
|
606 |
+
"epoch": 2.29,
|
607 |
+
"learning_rate": 0.00017927797030837768,
|
608 |
+
"loss": 0.1815,
|
609 |
+
"step": 100
|
610 |
+
},
|
611 |
+
{
|
612 |
+
"epoch": 2.31,
|
613 |
+
"learning_rate": 0.00017881653376756394,
|
614 |
+
"loss": 0.1818,
|
615 |
+
"step": 101
|
616 |
+
},
|
617 |
+
{
|
618 |
+
"epoch": 2.33,
|
619 |
+
"learning_rate": 0.0001783506237734019,
|
620 |
+
"loss": 0.1649,
|
621 |
+
"step": 102
|
622 |
+
},
|
623 |
+
{
|
624 |
+
"epoch": 2.35,
|
625 |
+
"learning_rate": 0.00017788026676991963,
|
626 |
+
"loss": 0.1684,
|
627 |
+
"step": 103
|
628 |
+
},
|
629 |
+
{
|
630 |
+
"epoch": 2.38,
|
631 |
+
"learning_rate": 0.00017740548945354752,
|
632 |
+
"loss": 0.1517,
|
633 |
+
"step": 104
|
634 |
+
},
|
635 |
+
{
|
636 |
+
"epoch": 2.4,
|
637 |
+
"learning_rate": 0.00017692631877160326,
|
638 |
+
"loss": 0.1871,
|
639 |
+
"step": 105
|
640 |
+
},
|
641 |
+
{
|
642 |
+
"epoch": 2.42,
|
643 |
+
"learning_rate": 0.0001764427819207624,
|
644 |
+
"loss": 0.1921,
|
645 |
+
"step": 106
|
646 |
+
},
|
647 |
+
{
|
648 |
+
"epoch": 2.45,
|
649 |
+
"learning_rate": 0.0001759549063455145,
|
650 |
+
"loss": 0.1659,
|
651 |
+
"step": 107
|
652 |
+
},
|
653 |
+
{
|
654 |
+
"epoch": 2.47,
|
655 |
+
"learning_rate": 0.00017546271973660574,
|
656 |
+
"loss": 0.1807,
|
657 |
+
"step": 108
|
658 |
+
},
|
659 |
+
{
|
660 |
+
"epoch": 2.49,
|
661 |
+
"learning_rate": 0.000174966250029467,
|
662 |
+
"loss": 0.1808,
|
663 |
+
"step": 109
|
664 |
+
},
|
665 |
+
{
|
666 |
+
"epoch": 2.51,
|
667 |
+
"learning_rate": 0.00017446552540262844,
|
668 |
+
"loss": 0.1844,
|
669 |
+
"step": 110
|
670 |
+
},
|
671 |
+
{
|
672 |
+
"epoch": 2.54,
|
673 |
+
"learning_rate": 0.0001739605742761201,
|
674 |
+
"loss": 0.174,
|
675 |
+
"step": 111
|
676 |
+
},
|
677 |
+
{
|
678 |
+
"epoch": 2.56,
|
679 |
+
"learning_rate": 0.00017345142530985887,
|
680 |
+
"loss": 0.1752,
|
681 |
+
"step": 112
|
682 |
+
},
|
683 |
+
{
|
684 |
+
"epoch": 2.58,
|
685 |
+
"learning_rate": 0.00017293810740202182,
|
686 |
+
"loss": 0.1788,
|
687 |
+
"step": 113
|
688 |
+
},
|
689 |
+
{
|
690 |
+
"epoch": 2.61,
|
691 |
+
"learning_rate": 0.00017242064968740598,
|
692 |
+
"loss": 0.1748,
|
693 |
+
"step": 114
|
694 |
+
},
|
695 |
+
{
|
696 |
+
"epoch": 2.63,
|
697 |
+
"learning_rate": 0.00017189908153577473,
|
698 |
+
"loss": 0.1711,
|
699 |
+
"step": 115
|
700 |
+
},
|
701 |
+
{
|
702 |
+
"epoch": 2.65,
|
703 |
+
"learning_rate": 0.0001713734325501908,
|
704 |
+
"loss": 0.1741,
|
705 |
+
"step": 116
|
706 |
+
},
|
707 |
+
{
|
708 |
+
"epoch": 2.67,
|
709 |
+
"learning_rate": 0.00017084373256533603,
|
710 |
+
"loss": 0.1779,
|
711 |
+
"step": 117
|
712 |
+
},
|
713 |
+
{
|
714 |
+
"epoch": 2.7,
|
715 |
+
"learning_rate": 0.00017031001164581828,
|
716 |
+
"loss": 0.1761,
|
717 |
+
"step": 118
|
718 |
+
},
|
719 |
+
{
|
720 |
+
"epoch": 2.72,
|
721 |
+
"learning_rate": 0.00016977230008446466,
|
722 |
+
"loss": 0.1771,
|
723 |
+
"step": 119
|
724 |
+
},
|
725 |
+
{
|
726 |
+
"epoch": 2.74,
|
727 |
+
"learning_rate": 0.00016923062840060234,
|
728 |
+
"loss": 0.1682,
|
729 |
+
"step": 120
|
730 |
+
},
|
731 |
+
{
|
732 |
+
"epoch": 2.77,
|
733 |
+
"learning_rate": 0.00016868502733832644,
|
734 |
+
"loss": 0.175,
|
735 |
+
"step": 121
|
736 |
+
},
|
737 |
+
{
|
738 |
+
"epoch": 2.79,
|
739 |
+
"learning_rate": 0.00016813552786475495,
|
740 |
+
"loss": 0.1804,
|
741 |
+
"step": 122
|
742 |
+
},
|
743 |
+
{
|
744 |
+
"epoch": 2.81,
|
745 |
+
"learning_rate": 0.00016758216116827105,
|
746 |
+
"loss": 0.1724,
|
747 |
+
"step": 123
|
748 |
+
},
|
749 |
+
{
|
750 |
+
"epoch": 2.83,
|
751 |
+
"learning_rate": 0.0001670249586567531,
|
752 |
+
"loss": 0.2074,
|
753 |
+
"step": 124
|
754 |
+
},
|
755 |
+
{
|
756 |
+
"epoch": 2.86,
|
757 |
+
"learning_rate": 0.00016646395195579178,
|
758 |
+
"loss": 0.1881,
|
759 |
+
"step": 125
|
760 |
+
},
|
761 |
+
{
|
762 |
+
"epoch": 2.88,
|
763 |
+
"learning_rate": 0.00016589917290689532,
|
764 |
+
"loss": 0.1791,
|
765 |
+
"step": 126
|
766 |
+
},
|
767 |
+
{
|
768 |
+
"epoch": 2.9,
|
769 |
+
"learning_rate": 0.00016533065356568206,
|
770 |
+
"loss": 0.1841,
|
771 |
+
"step": 127
|
772 |
+
},
|
773 |
+
{
|
774 |
+
"epoch": 2.93,
|
775 |
+
"learning_rate": 0.00016475842620006118,
|
776 |
+
"loss": 0.1779,
|
777 |
+
"step": 128
|
778 |
+
},
|
779 |
+
{
|
780 |
+
"epoch": 2.95,
|
781 |
+
"learning_rate": 0.0001641825232884011,
|
782 |
+
"loss": 0.1812,
|
783 |
+
"step": 129
|
784 |
+
},
|
785 |
+
{
|
786 |
+
"epoch": 2.97,
|
787 |
+
"learning_rate": 0.0001636029775176862,
|
788 |
+
"loss": 0.1699,
|
789 |
+
"step": 130
|
790 |
+
},
|
791 |
+
{
|
792 |
+
"epoch": 2.99,
|
793 |
+
"learning_rate": 0.0001630198217816616,
|
794 |
+
"loss": 0.1741,
|
795 |
+
"step": 131
|
796 |
+
},
|
797 |
+
{
|
798 |
+
"epoch": 3.02,
|
799 |
+
"learning_rate": 0.000162433089178966,
|
800 |
+
"loss": 0.1683,
|
801 |
+
"step": 132
|
802 |
+
},
|
803 |
+
{
|
804 |
+
"epoch": 3.04,
|
805 |
+
"learning_rate": 0.0001618428130112533,
|
806 |
+
"loss": 0.1808,
|
807 |
+
"step": 133
|
808 |
+
},
|
809 |
+
{
|
810 |
+
"epoch": 3.06,
|
811 |
+
"learning_rate": 0.0001612490267813023,
|
812 |
+
"loss": 0.1663,
|
813 |
+
"step": 134
|
814 |
+
},
|
815 |
+
{
|
816 |
+
"epoch": 3.09,
|
817 |
+
"learning_rate": 0.0001606517641911153,
|
818 |
+
"loss": 0.1684,
|
819 |
+
"step": 135
|
820 |
+
},
|
821 |
+
{
|
822 |
+
"epoch": 3.11,
|
823 |
+
"learning_rate": 0.00016005105914000507,
|
824 |
+
"loss": 0.1675,
|
825 |
+
"step": 136
|
826 |
+
},
|
827 |
+
{
|
828 |
+
"epoch": 3.13,
|
829 |
+
"learning_rate": 0.00015944694572267096,
|
830 |
+
"loss": 0.1706,
|
831 |
+
"step": 137
|
832 |
+
},
|
833 |
+
{
|
834 |
+
"epoch": 3.15,
|
835 |
+
"learning_rate": 0.00015883945822726372,
|
836 |
+
"loss": 0.1773,
|
837 |
+
"step": 138
|
838 |
+
},
|
839 |
+
{
|
840 |
+
"epoch": 3.18,
|
841 |
+
"learning_rate": 0.00015822863113343935,
|
842 |
+
"loss": 0.1763,
|
843 |
+
"step": 139
|
844 |
+
},
|
845 |
+
{
|
846 |
+
"epoch": 3.2,
|
847 |
+
"learning_rate": 0.00015761449911040208,
|
848 |
+
"loss": 0.1799,
|
849 |
+
"step": 140
|
850 |
+
},
|
851 |
+
{
|
852 |
+
"epoch": 3.22,
|
853 |
+
"learning_rate": 0.00015699709701493667,
|
854 |
+
"loss": 0.1684,
|
855 |
+
"step": 141
|
856 |
+
},
|
857 |
+
{
|
858 |
+
"epoch": 3.25,
|
859 |
+
"learning_rate": 0.0001563764598894301,
|
860 |
+
"loss": 0.1742,
|
861 |
+
"step": 142
|
862 |
+
},
|
863 |
+
{
|
864 |
+
"epoch": 3.27,
|
865 |
+
"learning_rate": 0.0001557526229598824,
|
866 |
+
"loss": 0.1751,
|
867 |
+
"step": 143
|
868 |
+
},
|
869 |
+
{
|
870 |
+
"epoch": 3.29,
|
871 |
+
"learning_rate": 0.0001551256216339076,
|
872 |
+
"loss": 0.1754,
|
873 |
+
"step": 144
|
874 |
+
},
|
875 |
+
{
|
876 |
+
"epoch": 3.31,
|
877 |
+
"learning_rate": 0.00015449549149872376,
|
878 |
+
"loss": 0.1764,
|
879 |
+
"step": 145
|
880 |
+
},
|
881 |
+
{
|
882 |
+
"epoch": 3.34,
|
883 |
+
"learning_rate": 0.00015386226831913348,
|
884 |
+
"loss": 0.1703,
|
885 |
+
"step": 146
|
886 |
+
},
|
887 |
+
{
|
888 |
+
"epoch": 3.36,
|
889 |
+
"learning_rate": 0.00015322598803549356,
|
890 |
+
"loss": 0.1731,
|
891 |
+
"step": 147
|
892 |
+
},
|
893 |
+
{
|
894 |
+
"epoch": 3.38,
|
895 |
+
"learning_rate": 0.00015258668676167546,
|
896 |
+
"loss": 0.1741,
|
897 |
+
"step": 148
|
898 |
+
},
|
899 |
+
{
|
900 |
+
"epoch": 3.41,
|
901 |
+
"learning_rate": 0.00015194440078301536,
|
902 |
+
"loss": 0.1703,
|
903 |
+
"step": 149
|
904 |
+
},
|
905 |
+
{
|
906 |
+
"epoch": 3.43,
|
907 |
+
"learning_rate": 0.00015129916655425468,
|
908 |
+
"loss": 0.167,
|
909 |
+
"step": 150
|
910 |
+
},
|
911 |
+
{
|
912 |
+
"epoch": 3.45,
|
913 |
+
"learning_rate": 0.00015065102069747118,
|
914 |
+
"loss": 0.1876,
|
915 |
+
"step": 151
|
916 |
+
},
|
917 |
+
{
|
918 |
+
"epoch": 3.47,
|
919 |
+
"learning_rate": 0.00015000000000000001,
|
920 |
+
"loss": 0.1761,
|
921 |
+
"step": 152
|
922 |
+
},
|
923 |
+
{
|
924 |
+
"epoch": 3.5,
|
925 |
+
"learning_rate": 0.00014934614141234618,
|
926 |
+
"loss": 0.1592,
|
927 |
+
"step": 153
|
928 |
+
},
|
929 |
+
{
|
930 |
+
"epoch": 3.52,
|
931 |
+
"learning_rate": 0.000148689482046087,
|
932 |
+
"loss": 0.1581,
|
933 |
+
"step": 154
|
934 |
+
},
|
935 |
+
{
|
936 |
+
"epoch": 3.54,
|
937 |
+
"learning_rate": 0.00014803005917176585,
|
938 |
+
"loss": 0.1804,
|
939 |
+
"step": 155
|
940 |
+
},
|
941 |
+
{
|
942 |
+
"epoch": 3.57,
|
943 |
+
"learning_rate": 0.00014736791021677676,
|
944 |
+
"loss": 0.1699,
|
945 |
+
"step": 156
|
946 |
+
},
|
947 |
+
{
|
948 |
+
"epoch": 3.59,
|
949 |
+
"learning_rate": 0.0001467030727632401,
|
950 |
+
"loss": 0.2209,
|
951 |
+
"step": 157
|
952 |
+
},
|
953 |
+
{
|
954 |
+
"epoch": 3.61,
|
955 |
+
"learning_rate": 0.0001460355845458695,
|
956 |
+
"loss": 0.177,
|
957 |
+
"step": 158
|
958 |
+
},
|
959 |
+
{
|
960 |
+
"epoch": 3.63,
|
961 |
+
"learning_rate": 0.00014536548344983016,
|
962 |
+
"loss": 0.1828,
|
963 |
+
"step": 159
|
964 |
+
},
|
965 |
+
{
|
966 |
+
"epoch": 3.66,
|
967 |
+
"learning_rate": 0.00014469280750858854,
|
968 |
+
"loss": 0.1725,
|
969 |
+
"step": 160
|
970 |
+
},
|
971 |
+
{
|
972 |
+
"epoch": 3.68,
|
973 |
+
"learning_rate": 0.00014401759490175362,
|
974 |
+
"loss": 0.1645,
|
975 |
+
"step": 161
|
976 |
+
},
|
977 |
+
{
|
978 |
+
"epoch": 3.7,
|
979 |
+
"learning_rate": 0.00014333988395290992,
|
980 |
+
"loss": 0.1754,
|
981 |
+
"step": 162
|
982 |
+
},
|
983 |
+
{
|
984 |
+
"epoch": 3.73,
|
985 |
+
"learning_rate": 0.00014265971312744252,
|
986 |
+
"loss": 0.1867,
|
987 |
+
"step": 163
|
988 |
+
},
|
989 |
+
{
|
990 |
+
"epoch": 3.75,
|
991 |
+
"learning_rate": 0.00014197712103035346,
|
992 |
+
"loss": 0.1735,
|
993 |
+
"step": 164
|
994 |
+
},
|
995 |
+
{
|
996 |
+
"epoch": 3.77,
|
997 |
+
"learning_rate": 0.00014129214640407102,
|
998 |
+
"loss": 0.1767,
|
999 |
+
"step": 165
|
1000 |
+
},
|
1001 |
+
{
|
1002 |
+
"epoch": 3.79,
|
1003 |
+
"learning_rate": 0.00014060482812625055,
|
1004 |
+
"loss": 0.1657,
|
1005 |
+
"step": 166
|
1006 |
+
},
|
1007 |
+
{
|
1008 |
+
"epoch": 3.82,
|
1009 |
+
"learning_rate": 0.0001399152052075679,
|
1010 |
+
"loss": 0.1734,
|
1011 |
+
"step": 167
|
1012 |
+
},
|
1013 |
+
{
|
1014 |
+
"epoch": 3.84,
|
1015 |
+
"learning_rate": 0.00013922331678950525,
|
1016 |
+
"loss": 0.1821,
|
1017 |
+
"step": 168
|
1018 |
+
},
|
1019 |
+
{
|
1020 |
+
"epoch": 3.86,
|
1021 |
+
"learning_rate": 0.00013852920214212964,
|
1022 |
+
"loss": 0.1839,
|
1023 |
+
"step": 169
|
1024 |
+
},
|
1025 |
+
{
|
1026 |
+
"epoch": 3.89,
|
1027 |
+
"learning_rate": 0.00013783290066186391,
|
1028 |
+
"loss": 0.1958,
|
1029 |
+
"step": 170
|
1030 |
+
},
|
1031 |
+
{
|
1032 |
+
"epoch": 3.91,
|
1033 |
+
"learning_rate": 0.00013713445186925075,
|
1034 |
+
"loss": 0.1815,
|
1035 |
+
"step": 171
|
1036 |
+
},
|
1037 |
+
{
|
1038 |
+
"epoch": 3.93,
|
1039 |
+
"learning_rate": 0.00013643389540670962,
|
1040 |
+
"loss": 0.1716,
|
1041 |
+
"step": 172
|
1042 |
+
},
|
1043 |
+
{
|
1044 |
+
"epoch": 3.95,
|
1045 |
+
"learning_rate": 0.00013573127103628667,
|
1046 |
+
"loss": 0.1688,
|
1047 |
+
"step": 173
|
1048 |
+
},
|
1049 |
+
{
|
1050 |
+
"epoch": 3.98,
|
1051 |
+
"learning_rate": 0.00013502661863739793,
|
1052 |
+
"loss": 0.1664,
|
1053 |
+
"step": 174
|
1054 |
+
},
|
1055 |
+
{
|
1056 |
+
"epoch": 4.0,
|
1057 |
+
"learning_rate": 0.00013431997820456592,
|
1058 |
+
"loss": 0.1638,
|
1059 |
+
"step": 175
|
1060 |
+
},
|
1061 |
+
{
|
1062 |
+
"epoch": 4.02,
|
1063 |
+
"learning_rate": 0.0001336113898451496,
|
1064 |
+
"loss": 0.2074,
|
1065 |
+
"step": 176
|
1066 |
+
},
|
1067 |
+
{
|
1068 |
+
"epoch": 4.05,
|
1069 |
+
"learning_rate": 0.0001329008937770679,
|
1070 |
+
"loss": 0.1675,
|
1071 |
+
"step": 177
|
1072 |
+
},
|
1073 |
+
{
|
1074 |
+
"epoch": 4.07,
|
1075 |
+
"learning_rate": 0.0001321885303265172,
|
1076 |
+
"loss": 0.1556,
|
1077 |
+
"step": 178
|
1078 |
+
},
|
1079 |
+
{
|
1080 |
+
"epoch": 4.09,
|
1081 |
+
"learning_rate": 0.00013147433992568227,
|
1082 |
+
"loss": 0.1653,
|
1083 |
+
"step": 179
|
1084 |
+
},
|
1085 |
+
{
|
1086 |
+
"epoch": 4.11,
|
1087 |
+
"learning_rate": 0.00013075836311044175,
|
1088 |
+
"loss": 0.1603,
|
1089 |
+
"step": 180
|
1090 |
+
},
|
1091 |
+
{
|
1092 |
+
"epoch": 4.14,
|
1093 |
+
"learning_rate": 0.0001300406405180671,
|
1094 |
+
"loss": 0.1758,
|
1095 |
+
"step": 181
|
1096 |
+
},
|
1097 |
+
{
|
1098 |
+
"epoch": 4.16,
|
1099 |
+
"learning_rate": 0.0001293212128849163,
|
1100 |
+
"loss": 0.1949,
|
1101 |
+
"step": 182
|
1102 |
+
},
|
1103 |
+
{
|
1104 |
+
"epoch": 4.18,
|
1105 |
+
"learning_rate": 0.00012860012104412165,
|
1106 |
+
"loss": 0.17,
|
1107 |
+
"step": 183
|
1108 |
+
},
|
1109 |
+
{
|
1110 |
+
"epoch": 4.21,
|
1111 |
+
"learning_rate": 0.0001278774059232723,
|
1112 |
+
"loss": 0.1662,
|
1113 |
+
"step": 184
|
1114 |
+
},
|
1115 |
+
{
|
1116 |
+
"epoch": 4.23,
|
1117 |
+
"learning_rate": 0.00012715310854209124,
|
1118 |
+
"loss": 0.1571,
|
1119 |
+
"step": 185
|
1120 |
+
},
|
1121 |
+
{
|
1122 |
+
"epoch": 4.25,
|
1123 |
+
"learning_rate": 0.00012642727001010694,
|
1124 |
+
"loss": 0.1979,
|
1125 |
+
"step": 186
|
1126 |
+
},
|
1127 |
+
{
|
1128 |
+
"epoch": 4.27,
|
1129 |
+
"learning_rate": 0.00012569993152432028,
|
1130 |
+
"loss": 0.1666,
|
1131 |
+
"step": 187
|
1132 |
+
},
|
1133 |
+
{
|
1134 |
+
"epoch": 4.3,
|
1135 |
+
"learning_rate": 0.00012497113436686627,
|
1136 |
+
"loss": 0.1065,
|
1137 |
+
"step": 188
|
1138 |
+
},
|
1139 |
+
{
|
1140 |
+
"epoch": 4.32,
|
1141 |
+
"learning_rate": 0.00012424091990267087,
|
1142 |
+
"loss": 0.1146,
|
1143 |
+
"step": 189
|
1144 |
+
},
|
1145 |
+
{
|
1146 |
+
"epoch": 4.34,
|
1147 |
+
"learning_rate": 0.0001235093295771032,
|
1148 |
+
"loss": 0.1749,
|
1149 |
+
"step": 190
|
1150 |
+
},
|
1151 |
+
{
|
1152 |
+
"epoch": 4.37,
|
1153 |
+
"learning_rate": 0.00012277640491362341,
|
1154 |
+
"loss": 0.1256,
|
1155 |
+
"step": 191
|
1156 |
+
},
|
1157 |
+
{
|
1158 |
+
"epoch": 4.39,
|
1159 |
+
"learning_rate": 0.0001220421875114256,
|
1160 |
+
"loss": 0.1835,
|
1161 |
+
"step": 192
|
1162 |
+
},
|
1163 |
+
{
|
1164 |
+
"epoch": 4.41,
|
1165 |
+
"learning_rate": 0.0001213067190430769,
|
1166 |
+
"loss": 0.1628,
|
1167 |
+
"step": 193
|
1168 |
+
},
|
1169 |
+
{
|
1170 |
+
"epoch": 4.43,
|
1171 |
+
"learning_rate": 0.00012057004125215223,
|
1172 |
+
"loss": 0.256,
|
1173 |
+
"step": 194
|
1174 |
+
},
|
1175 |
+
{
|
1176 |
+
"epoch": 4.46,
|
1177 |
+
"learning_rate": 0.00011983219595086506,
|
1178 |
+
"loss": 0.146,
|
1179 |
+
"step": 195
|
1180 |
+
},
|
1181 |
+
{
|
1182 |
+
"epoch": 4.48,
|
1183 |
+
"learning_rate": 0.00011909322501769406,
|
1184 |
+
"loss": 0.1682,
|
1185 |
+
"step": 196
|
1186 |
+
},
|
1187 |
+
{
|
1188 |
+
"epoch": 4.5,
|
1189 |
+
"learning_rate": 0.0001183531703950064,
|
1190 |
+
"loss": 0.1794,
|
1191 |
+
"step": 197
|
1192 |
+
},
|
1193 |
+
{
|
1194 |
+
"epoch": 4.53,
|
1195 |
+
"learning_rate": 0.00011761207408667703,
|
1196 |
+
"loss": 0.1905,
|
1197 |
+
"step": 198
|
1198 |
+
},
|
1199 |
+
{
|
1200 |
+
"epoch": 4.55,
|
1201 |
+
"learning_rate": 0.00011686997815570473,
|
1202 |
+
"loss": 0.1749,
|
1203 |
+
"step": 199
|
1204 |
+
},
|
1205 |
+
{
|
1206 |
+
"epoch": 4.57,
|
1207 |
+
"learning_rate": 0.00011612692472182463,
|
1208 |
+
"loss": 0.1775,
|
1209 |
+
"step": 200
|
1210 |
+
},
|
1211 |
+
{
|
1212 |
+
"epoch": 4.59,
|
1213 |
+
"learning_rate": 0.00011538295595911764,
|
1214 |
+
"loss": 0.1672,
|
1215 |
+
"step": 201
|
1216 |
+
},
|
1217 |
+
{
|
1218 |
+
"epoch": 4.62,
|
1219 |
+
"learning_rate": 0.00011463811409361667,
|
1220 |
+
"loss": 0.2042,
|
1221 |
+
"step": 202
|
1222 |
+
},
|
1223 |
+
{
|
1224 |
+
"epoch": 4.64,
|
1225 |
+
"learning_rate": 0.00011389244140091013,
|
1226 |
+
"loss": 0.1714,
|
1227 |
+
"step": 203
|
1228 |
+
},
|
1229 |
+
{
|
1230 |
+
"epoch": 4.66,
|
1231 |
+
"learning_rate": 0.00011314598020374231,
|
1232 |
+
"loss": 0.1637,
|
1233 |
+
"step": 204
|
1234 |
+
},
|
1235 |
+
{
|
1236 |
+
"epoch": 4.69,
|
1237 |
+
"learning_rate": 0.00011239877286961122,
|
1238 |
+
"loss": 0.1786,
|
1239 |
+
"step": 205
|
1240 |
+
},
|
1241 |
+
{
|
1242 |
+
"epoch": 4.71,
|
1243 |
+
"learning_rate": 0.00011165086180836406,
|
1244 |
+
"loss": 0.175,
|
1245 |
+
"step": 206
|
1246 |
+
},
|
1247 |
+
{
|
1248 |
+
"epoch": 4.73,
|
1249 |
+
"learning_rate": 0.00011090228946979,
|
1250 |
+
"loss": 0.1763,
|
1251 |
+
"step": 207
|
1252 |
+
},
|
1253 |
+
{
|
1254 |
+
"epoch": 4.75,
|
1255 |
+
"learning_rate": 0.00011015309834121081,
|
1256 |
+
"loss": 0.1941,
|
1257 |
+
"step": 208
|
1258 |
+
},
|
1259 |
+
{
|
1260 |
+
"epoch": 4.78,
|
1261 |
+
"learning_rate": 0.00010940333094506952,
|
1262 |
+
"loss": 0.1452,
|
1263 |
+
"step": 209
|
1264 |
+
},
|
1265 |
+
{
|
1266 |
+
"epoch": 4.8,
|
1267 |
+
"learning_rate": 0.00010865302983651673,
|
1268 |
+
"loss": 0.1719,
|
1269 |
+
"step": 210
|
1270 |
+
},
|
1271 |
+
{
|
1272 |
+
"epoch": 4.82,
|
1273 |
+
"learning_rate": 0.00010790223760099549,
|
1274 |
+
"loss": 0.1697,
|
1275 |
+
"step": 211
|
1276 |
+
},
|
1277 |
+
{
|
1278 |
+
"epoch": 4.85,
|
1279 |
+
"learning_rate": 0.00010715099685182408,
|
1280 |
+
"loss": 0.1644,
|
1281 |
+
"step": 212
|
1282 |
+
},
|
1283 |
+
{
|
1284 |
+
"epoch": 4.87,
|
1285 |
+
"learning_rate": 0.00010639935022777741,
|
1286 |
+
"loss": 0.1683,
|
1287 |
+
"step": 213
|
1288 |
+
},
|
1289 |
+
{
|
1290 |
+
"epoch": 4.89,
|
1291 |
+
"learning_rate": 0.00010564734039066699,
|
1292 |
+
"loss": 0.1746,
|
1293 |
+
"step": 214
|
1294 |
+
},
|
1295 |
+
{
|
1296 |
+
"epoch": 4.91,
|
1297 |
+
"learning_rate": 0.00010489501002291952,
|
1298 |
+
"loss": 0.1606,
|
1299 |
+
"step": 215
|
1300 |
+
},
|
1301 |
+
{
|
1302 |
+
"epoch": 4.94,
|
1303 |
+
"learning_rate": 0.00010414240182515429,
|
1304 |
+
"loss": 0.1841,
|
1305 |
+
"step": 216
|
1306 |
+
},
|
1307 |
+
{
|
1308 |
+
"epoch": 4.96,
|
1309 |
+
"learning_rate": 0.00010338955851375962,
|
1310 |
+
"loss": 0.1833,
|
1311 |
+
"step": 217
|
1312 |
+
},
|
1313 |
+
{
|
1314 |
+
"epoch": 4.98,
|
1315 |
+
"learning_rate": 0.00010263652281846837,
|
1316 |
+
"loss": 0.1802,
|
1317 |
+
"step": 218
|
1318 |
+
},
|
1319 |
+
{
|
1320 |
+
"epoch": 5.01,
|
1321 |
+
"learning_rate": 0.00010188333747993264,
|
1322 |
+
"loss": 0.1675,
|
1323 |
+
"step": 219
|
1324 |
+
},
|
1325 |
+
{
|
1326 |
+
"epoch": 5.03,
|
1327 |
+
"learning_rate": 0.00010113004524729799,
|
1328 |
+
"loss": 0.1598,
|
1329 |
+
"step": 220
|
1330 |
+
},
|
1331 |
+
{
|
1332 |
+
"epoch": 5.05,
|
1333 |
+
"learning_rate": 0.00010037668887577709,
|
1334 |
+
"loss": 0.1612,
|
1335 |
+
"step": 221
|
1336 |
+
},
|
1337 |
+
{
|
1338 |
+
"epoch": 5.07,
|
1339 |
+
"learning_rate": 9.962331112422293e-05,
|
1340 |
+
"loss": 0.1812,
|
1341 |
+
"step": 222
|
1342 |
+
},
|
1343 |
+
{
|
1344 |
+
"epoch": 5.1,
|
1345 |
+
"learning_rate": 9.886995475270205e-05,
|
1346 |
+
"loss": 0.1853,
|
1347 |
+
"step": 223
|
1348 |
+
},
|
1349 |
+
{
|
1350 |
+
"epoch": 5.12,
|
1351 |
+
"learning_rate": 9.811666252006742e-05,
|
1352 |
+
"loss": 0.1369,
|
1353 |
+
"step": 224
|
1354 |
+
},
|
1355 |
+
{
|
1356 |
+
"epoch": 5.14,
|
1357 |
+
"learning_rate": 9.73634771815317e-05,
|
1358 |
+
"loss": 0.1563,
|
1359 |
+
"step": 225
|
1360 |
+
},
|
1361 |
+
{
|
1362 |
+
"epoch": 5.17,
|
1363 |
+
"learning_rate": 9.661044148624037e-05,
|
1364 |
+
"loss": 0.1466,
|
1365 |
+
"step": 226
|
1366 |
+
},
|
1367 |
+
{
|
1368 |
+
"epoch": 5.19,
|
1369 |
+
"learning_rate": 9.58575981748457e-05,
|
1370 |
+
"loss": 0.1343,
|
1371 |
+
"step": 227
|
1372 |
+
},
|
1373 |
+
{
|
1374 |
+
"epoch": 5.21,
|
1375 |
+
"learning_rate": 9.510498997708049e-05,
|
1376 |
+
"loss": 0.1231,
|
1377 |
+
"step": 228
|
1378 |
+
},
|
1379 |
+
{
|
1380 |
+
"epoch": 5.23,
|
1381 |
+
"learning_rate": 9.435265960933302e-05,
|
1382 |
+
"loss": 0.1472,
|
1383 |
+
"step": 229
|
1384 |
+
},
|
1385 |
+
{
|
1386 |
+
"epoch": 5.26,
|
1387 |
+
"learning_rate": 9.360064977222262e-05,
|
1388 |
+
"loss": 0.1681,
|
1389 |
+
"step": 230
|
1390 |
+
},
|
1391 |
+
{
|
1392 |
+
"epoch": 5.28,
|
1393 |
+
"learning_rate": 9.284900314817597e-05,
|
1394 |
+
"loss": 0.2364,
|
1395 |
+
"step": 231
|
1396 |
+
},
|
1397 |
+
{
|
1398 |
+
"epoch": 5.3,
|
1399 |
+
"learning_rate": 9.209776239900453e-05,
|
1400 |
+
"loss": 0.1228,
|
1401 |
+
"step": 232
|
1402 |
+
},
|
1403 |
+
{
|
1404 |
+
"epoch": 5.33,
|
1405 |
+
"learning_rate": 9.134697016348327e-05,
|
1406 |
+
"loss": 0.1417,
|
1407 |
+
"step": 233
|
1408 |
+
},
|
1409 |
+
{
|
1410 |
+
"epoch": 5.35,
|
1411 |
+
"learning_rate": 9.05966690549305e-05,
|
1412 |
+
"loss": 0.1512,
|
1413 |
+
"step": 234
|
1414 |
+
},
|
1415 |
+
{
|
1416 |
+
"epoch": 5.37,
|
1417 |
+
"learning_rate": 8.984690165878921e-05,
|
1418 |
+
"loss": 0.1248,
|
1419 |
+
"step": 235
|
1420 |
+
},
|
1421 |
+
{
|
1422 |
+
"epoch": 5.39,
|
1423 |
+
"learning_rate": 8.909771053021002e-05,
|
1424 |
+
"loss": 0.1252,
|
1425 |
+
"step": 236
|
1426 |
+
},
|
1427 |
+
{
|
1428 |
+
"epoch": 5.42,
|
1429 |
+
"learning_rate": 8.834913819163595e-05,
|
1430 |
+
"loss": 0.1341,
|
1431 |
+
"step": 237
|
1432 |
+
},
|
1433 |
+
{
|
1434 |
+
"epoch": 5.44,
|
1435 |
+
"learning_rate": 8.760122713038881e-05,
|
1436 |
+
"loss": 0.1644,
|
1437 |
+
"step": 238
|
1438 |
+
},
|
1439 |
+
{
|
1440 |
+
"epoch": 5.46,
|
1441 |
+
"learning_rate": 8.685401979625774e-05,
|
1442 |
+
"loss": 0.0977,
|
1443 |
+
"step": 239
|
1444 |
+
},
|
1445 |
+
{
|
1446 |
+
"epoch": 5.49,
|
1447 |
+
"learning_rate": 8.610755859908991e-05,
|
1448 |
+
"loss": 0.1699,
|
1449 |
+
"step": 240
|
1450 |
+
},
|
1451 |
+
{
|
1452 |
+
"epoch": 5.51,
|
1453 |
+
"learning_rate": 8.536188590638334e-05,
|
1454 |
+
"loss": 0.1196,
|
1455 |
+
"step": 241
|
1456 |
+
},
|
1457 |
+
{
|
1458 |
+
"epoch": 5.53,
|
1459 |
+
"learning_rate": 8.46170440408824e-05,
|
1460 |
+
"loss": 0.0777,
|
1461 |
+
"step": 242
|
1462 |
+
},
|
1463 |
+
{
|
1464 |
+
"epoch": 5.55,
|
1465 |
+
"learning_rate": 8.387307527817539e-05,
|
1466 |
+
"loss": 0.1266,
|
1467 |
+
"step": 243
|
1468 |
+
},
|
1469 |
+
{
|
1470 |
+
"epoch": 5.58,
|
1471 |
+
"learning_rate": 8.313002184429529e-05,
|
1472 |
+
"loss": 0.1463,
|
1473 |
+
"step": 244
|
1474 |
+
},
|
1475 |
+
{
|
1476 |
+
"epoch": 5.6,
|
1477 |
+
"learning_rate": 8.238792591332299e-05,
|
1478 |
+
"loss": 0.1037,
|
1479 |
+
"step": 245
|
1480 |
+
},
|
1481 |
+
{
|
1482 |
+
"epoch": 5.62,
|
1483 |
+
"learning_rate": 8.164682960499361e-05,
|
1484 |
+
"loss": 0.1385,
|
1485 |
+
"step": 246
|
1486 |
+
},
|
1487 |
+
{
|
1488 |
+
"epoch": 5.65,
|
1489 |
+
"learning_rate": 8.090677498230596e-05,
|
1490 |
+
"loss": 0.0932,
|
1491 |
+
"step": 247
|
1492 |
+
},
|
1493 |
+
{
|
1494 |
+
"epoch": 5.67,
|
1495 |
+
"learning_rate": 8.016780404913496e-05,
|
1496 |
+
"loss": 0.1294,
|
1497 |
+
"step": 248
|
1498 |
+
},
|
1499 |
+
{
|
1500 |
+
"epoch": 5.69,
|
1501 |
+
"learning_rate": 7.942995874784776e-05,
|
1502 |
+
"loss": 0.191,
|
1503 |
+
"step": 249
|
1504 |
+
},
|
1505 |
+
{
|
1506 |
+
"epoch": 5.71,
|
1507 |
+
"learning_rate": 7.869328095692312e-05,
|
1508 |
+
"loss": 0.1488,
|
1509 |
+
"step": 250
|
1510 |
+
},
|
1511 |
+
{
|
1512 |
+
"epoch": 5.74,
|
1513 |
+
"learning_rate": 7.795781248857443e-05,
|
1514 |
+
"loss": 0.1259,
|
1515 |
+
"step": 251
|
1516 |
+
},
|
1517 |
+
{
|
1518 |
+
"epoch": 5.76,
|
1519 |
+
"learning_rate": 7.72235950863766e-05,
|
1520 |
+
"loss": 0.1266,
|
1521 |
+
"step": 252
|
1522 |
+
},
|
1523 |
+
{
|
1524 |
+
"epoch": 5.78,
|
1525 |
+
"learning_rate": 7.64906704228968e-05,
|
1526 |
+
"loss": 0.1172,
|
1527 |
+
"step": 253
|
1528 |
+
},
|
1529 |
+
{
|
1530 |
+
"epoch": 5.81,
|
1531 |
+
"learning_rate": 7.575908009732918e-05,
|
1532 |
+
"loss": 0.1032,
|
1533 |
+
"step": 254
|
1534 |
+
},
|
1535 |
+
{
|
1536 |
+
"epoch": 5.83,
|
1537 |
+
"learning_rate": 7.502886563313376e-05,
|
1538 |
+
"loss": 0.0891,
|
1539 |
+
"step": 255
|
1540 |
+
},
|
1541 |
+
{
|
1542 |
+
"epoch": 5.85,
|
1543 |
+
"learning_rate": 7.430006847567972e-05,
|
1544 |
+
"loss": 0.0909,
|
1545 |
+
"step": 256
|
1546 |
+
},
|
1547 |
+
{
|
1548 |
+
"epoch": 5.87,
|
1549 |
+
"learning_rate": 7.357272998989308e-05,
|
1550 |
+
"loss": 0.1367,
|
1551 |
+
"step": 257
|
1552 |
+
},
|
1553 |
+
{
|
1554 |
+
"epoch": 5.9,
|
1555 |
+
"learning_rate": 7.284689145790878e-05,
|
1556 |
+
"loss": 0.0965,
|
1557 |
+
"step": 258
|
1558 |
+
},
|
1559 |
+
{
|
1560 |
+
"epoch": 5.92,
|
1561 |
+
"learning_rate": 7.21225940767277e-05,
|
1562 |
+
"loss": 0.1868,
|
1563 |
+
"step": 259
|
1564 |
+
},
|
1565 |
+
{
|
1566 |
+
"epoch": 5.94,
|
1567 |
+
"learning_rate": 7.139987895587836e-05,
|
1568 |
+
"loss": 0.3087,
|
1569 |
+
"step": 260
|
1570 |
+
},
|
1571 |
+
{
|
1572 |
+
"epoch": 5.97,
|
1573 |
+
"learning_rate": 7.067878711508375e-05,
|
1574 |
+
"loss": 0.1388,
|
1575 |
+
"step": 261
|
1576 |
+
},
|
1577 |
+
{
|
1578 |
+
"epoch": 5.99,
|
1579 |
+
"learning_rate": 6.995935948193294e-05,
|
1580 |
+
"loss": 0.142,
|
1581 |
+
"step": 262
|
1582 |
+
},
|
1583 |
+
{
|
1584 |
+
"epoch": 6.01,
|
1585 |
+
"learning_rate": 6.924163688955825e-05,
|
1586 |
+
"loss": 0.1212,
|
1587 |
+
"step": 263
|
1588 |
+
},
|
1589 |
+
{
|
1590 |
+
"epoch": 6.03,
|
1591 |
+
"learning_rate": 6.852566007431773e-05,
|
1592 |
+
"loss": 0.1369,
|
1593 |
+
"step": 264
|
1594 |
+
},
|
1595 |
+
{
|
1596 |
+
"epoch": 6.06,
|
1597 |
+
"learning_rate": 6.781146967348284e-05,
|
1598 |
+
"loss": 0.0927,
|
1599 |
+
"step": 265
|
1600 |
+
},
|
1601 |
+
{
|
1602 |
+
"epoch": 6.08,
|
1603 |
+
"learning_rate": 6.709910622293212e-05,
|
1604 |
+
"loss": 0.1146,
|
1605 |
+
"step": 266
|
1606 |
+
},
|
1607 |
+
{
|
1608 |
+
"epoch": 6.1,
|
1609 |
+
"learning_rate": 6.638861015485043e-05,
|
1610 |
+
"loss": 0.1059,
|
1611 |
+
"step": 267
|
1612 |
+
},
|
1613 |
+
{
|
1614 |
+
"epoch": 6.13,
|
1615 |
+
"learning_rate": 6.568002179543409e-05,
|
1616 |
+
"loss": 0.1108,
|
1617 |
+
"step": 268
|
1618 |
+
},
|
1619 |
+
{
|
1620 |
+
"epoch": 6.15,
|
1621 |
+
"learning_rate": 6.497338136260209e-05,
|
1622 |
+
"loss": 0.1333,
|
1623 |
+
"step": 269
|
1624 |
+
},
|
1625 |
+
{
|
1626 |
+
"epoch": 6.17,
|
1627 |
+
"learning_rate": 6.426872896371331e-05,
|
1628 |
+
"loss": 0.115,
|
1629 |
+
"step": 270
|
1630 |
+
},
|
1631 |
+
{
|
1632 |
+
"epoch": 6.19,
|
1633 |
+
"learning_rate": 6.356610459329038e-05,
|
1634 |
+
"loss": 0.0776,
|
1635 |
+
"step": 271
|
1636 |
+
},
|
1637 |
+
{
|
1638 |
+
"epoch": 6.22,
|
1639 |
+
"learning_rate": 6.286554813074925e-05,
|
1640 |
+
"loss": 0.1038,
|
1641 |
+
"step": 272
|
1642 |
+
},
|
1643 |
+
{
|
1644 |
+
"epoch": 6.24,
|
1645 |
+
"learning_rate": 6.21670993381361e-05,
|
1646 |
+
"loss": 0.0796,
|
1647 |
+
"step": 273
|
1648 |
+
},
|
1649 |
+
{
|
1650 |
+
"epoch": 6.26,
|
1651 |
+
"learning_rate": 6.147079785787038e-05,
|
1652 |
+
"loss": 0.0982,
|
1653 |
+
"step": 274
|
1654 |
+
},
|
1655 |
+
{
|
1656 |
+
"epoch": 6.29,
|
1657 |
+
"learning_rate": 6.0776683210494766e-05,
|
1658 |
+
"loss": 0.114,
|
1659 |
+
"step": 275
|
1660 |
+
},
|
1661 |
+
{
|
1662 |
+
"epoch": 6.31,
|
1663 |
+
"learning_rate": 6.0084794792432155e-05,
|
1664 |
+
"loss": 0.0922,
|
1665 |
+
"step": 276
|
1666 |
+
},
|
1667 |
+
{
|
1668 |
+
"epoch": 6.33,
|
1669 |
+
"learning_rate": 5.93951718737495e-05,
|
1670 |
+
"loss": 0.0725,
|
1671 |
+
"step": 277
|
1672 |
+
},
|
1673 |
+
{
|
1674 |
+
"epoch": 6.35,
|
1675 |
+
"learning_rate": 5.8707853595928985e-05,
|
1676 |
+
"loss": 0.0855,
|
1677 |
+
"step": 278
|
1678 |
+
},
|
1679 |
+
{
|
1680 |
+
"epoch": 6.38,
|
1681 |
+
"learning_rate": 5.802287896964658e-05,
|
1682 |
+
"loss": 0.1254,
|
1683 |
+
"step": 279
|
1684 |
+
},
|
1685 |
+
{
|
1686 |
+
"epoch": 6.4,
|
1687 |
+
"learning_rate": 5.734028687255751e-05,
|
1688 |
+
"loss": 0.1193,
|
1689 |
+
"step": 280
|
1690 |
+
},
|
1691 |
+
{
|
1692 |
+
"epoch": 6.42,
|
1693 |
+
"learning_rate": 5.666011604709005e-05,
|
1694 |
+
"loss": 0.1212,
|
1695 |
+
"step": 281
|
1696 |
+
},
|
1697 |
+
{
|
1698 |
+
"epoch": 6.45,
|
1699 |
+
"learning_rate": 5.598240509824642e-05,
|
1700 |
+
"loss": 0.1744,
|
1701 |
+
"step": 282
|
1702 |
+
},
|
1703 |
+
{
|
1704 |
+
"epoch": 6.47,
|
1705 |
+
"learning_rate": 5.530719249141147e-05,
|
1706 |
+
"loss": 0.062,
|
1707 |
+
"step": 283
|
1708 |
+
},
|
1709 |
+
{
|
1710 |
+
"epoch": 6.49,
|
1711 |
+
"learning_rate": 5.463451655016988e-05,
|
1712 |
+
"loss": 0.1408,
|
1713 |
+
"step": 284
|
1714 |
+
},
|
1715 |
+
{
|
1716 |
+
"epoch": 6.51,
|
1717 |
+
"learning_rate": 5.39644154541305e-05,
|
1718 |
+
"loss": 0.0819,
|
1719 |
+
"step": 285
|
1720 |
+
},
|
1721 |
+
{
|
1722 |
+
"epoch": 6.54,
|
1723 |
+
"learning_rate": 5.329692723675994e-05,
|
1724 |
+
"loss": 0.118,
|
1725 |
+
"step": 286
|
1726 |
+
},
|
1727 |
+
{
|
1728 |
+
"epoch": 6.56,
|
1729 |
+
"learning_rate": 5.263208978322326e-05,
|
1730 |
+
"loss": 0.0602,
|
1731 |
+
"step": 287
|
1732 |
+
},
|
1733 |
+
{
|
1734 |
+
"epoch": 6.58,
|
1735 |
+
"learning_rate": 5.1969940828234184e-05,
|
1736 |
+
"loss": 0.0708,
|
1737 |
+
"step": 288
|
1738 |
+
},
|
1739 |
+
{
|
1740 |
+
"epoch": 6.61,
|
1741 |
+
"learning_rate": 5.131051795391302e-05,
|
1742 |
+
"loss": 0.107,
|
1743 |
+
"step": 289
|
1744 |
+
},
|
1745 |
+
{
|
1746 |
+
"epoch": 6.63,
|
1747 |
+
"learning_rate": 5.065385858765383e-05,
|
1748 |
+
"loss": 0.0621,
|
1749 |
+
"step": 290
|
1750 |
+
},
|
1751 |
+
{
|
1752 |
+
"epoch": 6.65,
|
1753 |
+
"learning_rate": 5.000000000000002e-05,
|
1754 |
+
"loss": 0.0428,
|
1755 |
+
"step": 291
|
1756 |
+
},
|
1757 |
+
{
|
1758 |
+
"epoch": 6.67,
|
1759 |
+
"learning_rate": 4.934897930252886e-05,
|
1760 |
+
"loss": 0.111,
|
1761 |
+
"step": 292
|
1762 |
+
},
|
1763 |
+
{
|
1764 |
+
"epoch": 6.7,
|
1765 |
+
"learning_rate": 4.870083344574531e-05,
|
1766 |
+
"loss": 0.1184,
|
1767 |
+
"step": 293
|
1768 |
+
},
|
1769 |
+
{
|
1770 |
+
"epoch": 6.72,
|
1771 |
+
"learning_rate": 4.805559921698464e-05,
|
1772 |
+
"loss": 0.0919,
|
1773 |
+
"step": 294
|
1774 |
+
},
|
1775 |
+
{
|
1776 |
+
"epoch": 6.74,
|
1777 |
+
"learning_rate": 4.7413313238324556e-05,
|
1778 |
+
"loss": 0.0477,
|
1779 |
+
"step": 295
|
1780 |
+
},
|
1781 |
+
{
|
1782 |
+
"epoch": 6.77,
|
1783 |
+
"learning_rate": 4.6774011964506435e-05,
|
1784 |
+
"loss": 0.0738,
|
1785 |
+
"step": 296
|
1786 |
+
},
|
1787 |
+
{
|
1788 |
+
"epoch": 6.79,
|
1789 |
+
"learning_rate": 4.613773168086657e-05,
|
1790 |
+
"loss": 0.101,
|
1791 |
+
"step": 297
|
1792 |
+
},
|
1793 |
+
{
|
1794 |
+
"epoch": 6.81,
|
1795 |
+
"learning_rate": 4.550450850127625e-05,
|
1796 |
+
"loss": 0.0585,
|
1797 |
+
"step": 298
|
1798 |
+
},
|
1799 |
+
{
|
1800 |
+
"epoch": 6.83,
|
1801 |
+
"learning_rate": 4.4874378366092476e-05,
|
1802 |
+
"loss": 0.0443,
|
1803 |
+
"step": 299
|
1804 |
+
},
|
1805 |
+
{
|
1806 |
+
"epoch": 6.86,
|
1807 |
+
"learning_rate": 4.42473770401176e-05,
|
1808 |
+
"loss": 0.1272,
|
1809 |
+
"step": 300
|
1810 |
+
},
|
1811 |
+
{
|
1812 |
+
"epoch": 6.88,
|
1813 |
+
"learning_rate": 4.3623540110569935e-05,
|
1814 |
+
"loss": 0.1569,
|
1815 |
+
"step": 301
|
1816 |
+
},
|
1817 |
+
{
|
1818 |
+
"epoch": 6.9,
|
1819 |
+
"learning_rate": 4.300290298506333e-05,
|
1820 |
+
"loss": 0.0314,
|
1821 |
+
"step": 302
|
1822 |
+
},
|
1823 |
+
{
|
1824 |
+
"epoch": 6.93,
|
1825 |
+
"learning_rate": 4.238550088959796e-05,
|
1826 |
+
"loss": 0.1179,
|
1827 |
+
"step": 303
|
1828 |
+
},
|
1829 |
+
{
|
1830 |
+
"epoch": 6.95,
|
1831 |
+
"learning_rate": 4.1771368866560665e-05,
|
1832 |
+
"loss": 0.1037,
|
1833 |
+
"step": 304
|
1834 |
+
},
|
1835 |
+
{
|
1836 |
+
"epoch": 6.97,
|
1837 |
+
"learning_rate": 4.116054177273627e-05,
|
1838 |
+
"loss": 0.0898,
|
1839 |
+
"step": 305
|
1840 |
+
},
|
1841 |
+
{
|
1842 |
+
"epoch": 6.99,
|
1843 |
+
"learning_rate": 4.0553054277329074e-05,
|
1844 |
+
"loss": 0.1015,
|
1845 |
+
"step": 306
|
1846 |
+
},
|
1847 |
+
{
|
1848 |
+
"epoch": 7.02,
|
1849 |
+
"learning_rate": 3.9948940859994966e-05,
|
1850 |
+
"loss": 0.0652,
|
1851 |
+
"step": 307
|
1852 |
+
},
|
1853 |
+
{
|
1854 |
+
"epoch": 7.04,
|
1855 |
+
"learning_rate": 3.9348235808884724e-05,
|
1856 |
+
"loss": 0.0403,
|
1857 |
+
"step": 308
|
1858 |
+
},
|
1859 |
+
{
|
1860 |
+
"epoch": 7.06,
|
1861 |
+
"learning_rate": 3.875097321869768e-05,
|
1862 |
+
"loss": 0.0501,
|
1863 |
+
"step": 309
|
1864 |
+
},
|
1865 |
+
{
|
1866 |
+
"epoch": 7.09,
|
1867 |
+
"learning_rate": 3.815718698874672e-05,
|
1868 |
+
"loss": 0.0874,
|
1869 |
+
"step": 310
|
1870 |
+
},
|
1871 |
+
{
|
1872 |
+
"epoch": 7.11,
|
1873 |
+
"learning_rate": 3.7566910821034005e-05,
|
1874 |
+
"loss": 0.0336,
|
1875 |
+
"step": 311
|
1876 |
+
},
|
1877 |
+
{
|
1878 |
+
"epoch": 7.13,
|
1879 |
+
"learning_rate": 3.698017821833844e-05,
|
1880 |
+
"loss": 0.0606,
|
1881 |
+
"step": 312
|
1882 |
+
},
|
1883 |
+
{
|
1884 |
+
"epoch": 7.15,
|
1885 |
+
"learning_rate": 3.6397022482313805e-05,
|
1886 |
+
"loss": 0.0154,
|
1887 |
+
"step": 313
|
1888 |
+
},
|
1889 |
+
{
|
1890 |
+
"epoch": 7.18,
|
1891 |
+
"learning_rate": 3.5817476711598906e-05,
|
1892 |
+
"loss": 0.0232,
|
1893 |
+
"step": 314
|
1894 |
+
},
|
1895 |
+
{
|
1896 |
+
"epoch": 7.2,
|
1897 |
+
"learning_rate": 3.524157379993882e-05,
|
1898 |
+
"loss": 0.0202,
|
1899 |
+
"step": 315
|
1900 |
+
},
|
1901 |
+
{
|
1902 |
+
"epoch": 7.22,
|
1903 |
+
"learning_rate": 3.466934643431795e-05,
|
1904 |
+
"loss": 0.0991,
|
1905 |
+
"step": 316
|
1906 |
+
},
|
1907 |
+
{
|
1908 |
+
"epoch": 7.25,
|
1909 |
+
"learning_rate": 3.4100827093104694e-05,
|
1910 |
+
"loss": 0.1159,
|
1911 |
+
"step": 317
|
1912 |
+
},
|
1913 |
+
{
|
1914 |
+
"epoch": 7.27,
|
1915 |
+
"learning_rate": 3.353604804420821e-05,
|
1916 |
+
"loss": 0.012,
|
1917 |
+
"step": 318
|
1918 |
+
},
|
1919 |
+
{
|
1920 |
+
"epoch": 7.29,
|
1921 |
+
"learning_rate": 3.2975041343246936e-05,
|
1922 |
+
"loss": 0.0735,
|
1923 |
+
"step": 319
|
1924 |
+
},
|
1925 |
+
{
|
1926 |
+
"epoch": 7.31,
|
1927 |
+
"learning_rate": 3.241783883172895e-05,
|
1928 |
+
"loss": 0.0097,
|
1929 |
+
"step": 320
|
1930 |
+
},
|
1931 |
+
{
|
1932 |
+
"epoch": 7.34,
|
1933 |
+
"learning_rate": 3.186447213524508e-05,
|
1934 |
+
"loss": 0.03,
|
1935 |
+
"step": 321
|
1936 |
+
},
|
1937 |
+
{
|
1938 |
+
"epoch": 7.36,
|
1939 |
+
"learning_rate": 3.131497266167357e-05,
|
1940 |
+
"loss": 0.0764,
|
1941 |
+
"step": 322
|
1942 |
+
},
|
1943 |
+
{
|
1944 |
+
"epoch": 7.38,
|
1945 |
+
"learning_rate": 3.076937159939768e-05,
|
1946 |
+
"loss": 0.0166,
|
1947 |
+
"step": 323
|
1948 |
+
},
|
1949 |
+
{
|
1950 |
+
"epoch": 7.41,
|
1951 |
+
"learning_rate": 3.0227699915535367e-05,
|
1952 |
+
"loss": 0.1195,
|
1953 |
+
"step": 324
|
1954 |
+
},
|
1955 |
+
{
|
1956 |
+
"epoch": 7.43,
|
1957 |
+
"learning_rate": 2.968998835418174e-05,
|
1958 |
+
"loss": 0.117,
|
1959 |
+
"step": 325
|
1960 |
+
},
|
1961 |
+
{
|
1962 |
+
"epoch": 7.45,
|
1963 |
+
"learning_rate": 2.9156267434663963e-05,
|
1964 |
+
"loss": 0.0241,
|
1965 |
+
"step": 326
|
1966 |
+
},
|
1967 |
+
{
|
1968 |
+
"epoch": 7.47,
|
1969 |
+
"learning_rate": 2.862656744980926e-05,
|
1970 |
+
"loss": 0.0874,
|
1971 |
+
"step": 327
|
1972 |
+
},
|
1973 |
+
{
|
1974 |
+
"epoch": 7.5,
|
1975 |
+
"learning_rate": 2.81009184642253e-05,
|
1976 |
+
"loss": 0.062,
|
1977 |
+
"step": 328
|
1978 |
+
},
|
1979 |
+
{
|
1980 |
+
"epoch": 7.52,
|
1981 |
+
"learning_rate": 2.757935031259402e-05,
|
1982 |
+
"loss": 0.0262,
|
1983 |
+
"step": 329
|
1984 |
+
},
|
1985 |
+
{
|
1986 |
+
"epoch": 7.54,
|
1987 |
+
"learning_rate": 2.7061892597978177e-05,
|
1988 |
+
"loss": 0.1282,
|
1989 |
+
"step": 330
|
1990 |
+
},
|
1991 |
+
{
|
1992 |
+
"epoch": 7.57,
|
1993 |
+
"learning_rate": 2.6548574690141125e-05,
|
1994 |
+
"loss": 0.0045,
|
1995 |
+
"step": 331
|
1996 |
+
},
|
1997 |
+
{
|
1998 |
+
"epoch": 7.59,
|
1999 |
+
"learning_rate": 2.603942572387993e-05,
|
2000 |
+
"loss": 0.0423,
|
2001 |
+
"step": 332
|
2002 |
+
},
|
2003 |
+
{
|
2004 |
+
"epoch": 7.61,
|
2005 |
+
"learning_rate": 2.553447459737157e-05,
|
2006 |
+
"loss": 0.0448,
|
2007 |
+
"step": 333
|
2008 |
+
},
|
2009 |
+
{
|
2010 |
+
"epoch": 7.63,
|
2011 |
+
"learning_rate": 2.5033749970533015e-05,
|
2012 |
+
"loss": 0.0534,
|
2013 |
+
"step": 334
|
2014 |
+
},
|
2015 |
+
{
|
2016 |
+
"epoch": 7.66,
|
2017 |
+
"learning_rate": 2.4537280263394258e-05,
|
2018 |
+
"loss": 0.04,
|
2019 |
+
"step": 335
|
2020 |
+
},
|
2021 |
+
{
|
2022 |
+
"epoch": 7.68,
|
2023 |
+
"learning_rate": 2.4045093654485518e-05,
|
2024 |
+
"loss": 0.0356,
|
2025 |
+
"step": 336
|
2026 |
+
},
|
2027 |
+
{
|
2028 |
+
"epoch": 7.7,
|
2029 |
+
"learning_rate": 2.355721807923761e-05,
|
2030 |
+
"loss": 0.0786,
|
2031 |
+
"step": 337
|
2032 |
+
},
|
2033 |
+
{
|
2034 |
+
"epoch": 7.73,
|
2035 |
+
"learning_rate": 2.307368122839675e-05,
|
2036 |
+
"loss": 0.0441,
|
2037 |
+
"step": 338
|
2038 |
+
},
|
2039 |
+
{
|
2040 |
+
"epoch": 7.75,
|
2041 |
+
"learning_rate": 2.2594510546452507e-05,
|
2042 |
+
"loss": 0.0155,
|
2043 |
+
"step": 339
|
2044 |
+
},
|
2045 |
+
{
|
2046 |
+
"epoch": 7.77,
|
2047 |
+
"learning_rate": 2.2119733230080408e-05,
|
2048 |
+
"loss": 0.0217,
|
2049 |
+
"step": 340
|
2050 |
+
},
|
2051 |
+
{
|
2052 |
+
"epoch": 7.79,
|
2053 |
+
"learning_rate": 2.1649376226598106e-05,
|
2054 |
+
"loss": 0.0472,
|
2055 |
+
"step": 341
|
2056 |
+
},
|
2057 |
+
{
|
2058 |
+
"epoch": 7.82,
|
2059 |
+
"learning_rate": 2.1183466232436088e-05,
|
2060 |
+
"loss": 0.0354,
|
2061 |
+
"step": 342
|
2062 |
+
},
|
2063 |
+
{
|
2064 |
+
"epoch": 7.84,
|
2065 |
+
"learning_rate": 2.0722029691622336e-05,
|
2066 |
+
"loss": 0.0702,
|
2067 |
+
"step": 343
|
2068 |
+
},
|
2069 |
+
{
|
2070 |
+
"epoch": 7.86,
|
2071 |
+
"learning_rate": 2.026509279428137e-05,
|
2072 |
+
"loss": 0.0759,
|
2073 |
+
"step": 344
|
2074 |
+
},
|
2075 |
+
{
|
2076 |
+
"epoch": 7.89,
|
2077 |
+
"learning_rate": 1.9812681475147942e-05,
|
2078 |
+
"loss": 0.1333,
|
2079 |
+
"step": 345
|
2080 |
+
},
|
2081 |
+
{
|
2082 |
+
"epoch": 7.91,
|
2083 |
+
"learning_rate": 1.9364821412094857e-05,
|
2084 |
+
"loss": 0.0323,
|
2085 |
+
"step": 346
|
2086 |
+
},
|
2087 |
+
{
|
2088 |
+
"epoch": 7.93,
|
2089 |
+
"learning_rate": 1.8921538024675678e-05,
|
2090 |
+
"loss": 0.0105,
|
2091 |
+
"step": 347
|
2092 |
+
},
|
2093 |
+
{
|
2094 |
+
"epoch": 7.95,
|
2095 |
+
"learning_rate": 1.848285647268181e-05,
|
2096 |
+
"loss": 0.0554,
|
2097 |
+
"step": 348
|
2098 |
+
},
|
2099 |
+
{
|
2100 |
+
"epoch": 7.98,
|
2101 |
+
"learning_rate": 1.8048801654714688e-05,
|
2102 |
+
"loss": 0.045,
|
2103 |
+
"step": 349
|
2104 |
+
},
|
2105 |
+
{
|
2106 |
+
"epoch": 8.0,
|
2107 |
+
"learning_rate": 1.761939820677241e-05,
|
2108 |
+
"loss": 0.0068,
|
2109 |
+
"step": 350
|
2110 |
+
},
|
2111 |
+
{
|
2112 |
+
"epoch": 8.02,
|
2113 |
+
"learning_rate": 1.7194670500851616e-05,
|
2114 |
+
"loss": 0.024,
|
2115 |
+
"step": 351
|
2116 |
+
},
|
2117 |
+
{
|
2118 |
+
"epoch": 8.05,
|
2119 |
+
"learning_rate": 1.6774642643563953e-05,
|
2120 |
+
"loss": 0.0245,
|
2121 |
+
"step": 352
|
2122 |
+
},
|
2123 |
+
{
|
2124 |
+
"epoch": 8.07,
|
2125 |
+
"learning_rate": 1.6359338474768193e-05,
|
2126 |
+
"loss": 0.0177,
|
2127 |
+
"step": 353
|
2128 |
+
},
|
2129 |
+
{
|
2130 |
+
"epoch": 8.09,
|
2131 |
+
"learning_rate": 1.594878156621672e-05,
|
2132 |
+
"loss": 0.0234,
|
2133 |
+
"step": 354
|
2134 |
+
},
|
2135 |
+
{
|
2136 |
+
"epoch": 8.11,
|
2137 |
+
"learning_rate": 1.554299522021796e-05,
|
2138 |
+
"loss": 0.0174,
|
2139 |
+
"step": 355
|
2140 |
+
},
|
2141 |
+
{
|
2142 |
+
"epoch": 8.14,
|
2143 |
+
"learning_rate": 1.5142002468313699e-05,
|
2144 |
+
"loss": 0.0074,
|
2145 |
+
"step": 356
|
2146 |
+
},
|
2147 |
+
{
|
2148 |
+
"epoch": 8.16,
|
2149 |
+
"learning_rate": 1.4745826069971758e-05,
|
2150 |
+
"loss": 0.0468,
|
2151 |
+
"step": 357
|
2152 |
+
},
|
2153 |
+
{
|
2154 |
+
"epoch": 8.18,
|
2155 |
+
"learning_rate": 1.4354488511294417e-05,
|
2156 |
+
"loss": 0.0051,
|
2157 |
+
"step": 358
|
2158 |
+
},
|
2159 |
+
{
|
2160 |
+
"epoch": 8.21,
|
2161 |
+
"learning_rate": 1.3968012003741948e-05,
|
2162 |
+
"loss": 0.0042,
|
2163 |
+
"step": 359
|
2164 |
+
},
|
2165 |
+
{
|
2166 |
+
"epoch": 8.23,
|
2167 |
+
"learning_rate": 1.35864184828721e-05,
|
2168 |
+
"loss": 0.0071,
|
2169 |
+
"step": 360
|
2170 |
+
},
|
2171 |
+
{
|
2172 |
+
"epoch": 8.25,
|
2173 |
+
"learning_rate": 1.3209729607095023e-05,
|
2174 |
+
"loss": 0.0074,
|
2175 |
+
"step": 361
|
2176 |
+
},
|
2177 |
+
{
|
2178 |
+
"epoch": 8.27,
|
2179 |
+
"learning_rate": 1.2837966756443975e-05,
|
2180 |
+
"loss": 0.0087,
|
2181 |
+
"step": 362
|
2182 |
+
},
|
2183 |
+
{
|
2184 |
+
"epoch": 8.3,
|
2185 |
+
"learning_rate": 1.2471151031361794e-05,
|
2186 |
+
"loss": 0.0081,
|
2187 |
+
"step": 363
|
2188 |
+
},
|
2189 |
+
{
|
2190 |
+
"epoch": 8.32,
|
2191 |
+
"learning_rate": 1.2109303251503434e-05,
|
2192 |
+
"loss": 0.0068,
|
2193 |
+
"step": 364
|
2194 |
+
},
|
2195 |
+
{
|
2196 |
+
"epoch": 8.34,
|
2197 |
+
"learning_rate": 1.1752443954554082e-05,
|
2198 |
+
"loss": 0.0068,
|
2199 |
+
"step": 365
|
2200 |
+
},
|
2201 |
+
{
|
2202 |
+
"epoch": 8.37,
|
2203 |
+
"learning_rate": 1.1400593395063686e-05,
|
2204 |
+
"loss": 0.01,
|
2205 |
+
"step": 366
|
2206 |
+
},
|
2207 |
+
{
|
2208 |
+
"epoch": 8.39,
|
2209 |
+
"learning_rate": 1.1053771543297198e-05,
|
2210 |
+
"loss": 0.0078,
|
2211 |
+
"step": 367
|
2212 |
+
},
|
2213 |
+
{
|
2214 |
+
"epoch": 8.41,
|
2215 |
+
"learning_rate": 1.0711998084101205e-05,
|
2216 |
+
"loss": 0.0106,
|
2217 |
+
"step": 368
|
2218 |
+
},
|
2219 |
+
{
|
2220 |
+
"epoch": 8.43,
|
2221 |
+
"learning_rate": 1.0375292415786575e-05,
|
2222 |
+
"loss": 0.0035,
|
2223 |
+
"step": 369
|
2224 |
+
},
|
2225 |
+
{
|
2226 |
+
"epoch": 8.46,
|
2227 |
+
"learning_rate": 1.0043673649027518e-05,
|
2228 |
+
"loss": 0.0715,
|
2229 |
+
"step": 370
|
2230 |
+
},
|
2231 |
+
{
|
2232 |
+
"epoch": 8.48,
|
2233 |
+
"learning_rate": 9.717160605776932e-06,
|
2234 |
+
"loss": 0.0093,
|
2235 |
+
"step": 371
|
2236 |
+
},
|
2237 |
+
{
|
2238 |
+
"epoch": 8.5,
|
2239 |
+
"learning_rate": 9.39577181819794e-06,
|
2240 |
+
"loss": 0.0815,
|
2241 |
+
"step": 372
|
2242 |
+
},
|
2243 |
+
{
|
2244 |
+
"epoch": 8.53,
|
2245 |
+
"learning_rate": 9.07952552761232e-06,
|
2246 |
+
"loss": 0.0086,
|
2247 |
+
"step": 373
|
2248 |
+
},
|
2249 |
+
{
|
2250 |
+
"epoch": 8.55,
|
2251 |
+
"learning_rate": 8.768439683464868e-06,
|
2252 |
+
"loss": 0.0138,
|
2253 |
+
"step": 374
|
2254 |
+
},
|
2255 |
+
{
|
2256 |
+
"epoch": 8.57,
|
2257 |
+
"learning_rate": 8.462531942304896e-06,
|
2258 |
+
"loss": 0.0132,
|
2259 |
+
"step": 375
|
2260 |
+
},
|
2261 |
+
{
|
2262 |
+
"epoch": 8.59,
|
2263 |
+
"learning_rate": 8.161819666783888e-06,
|
2264 |
+
"loss": 0.0141,
|
2265 |
+
"step": 376
|
2266 |
+
},
|
2267 |
+
{
|
2268 |
+
"epoch": 8.62,
|
2269 |
+
"learning_rate": 7.866319924670163e-06,
|
2270 |
+
"loss": 0.0477,
|
2271 |
+
"step": 377
|
2272 |
+
},
|
2273 |
+
{
|
2274 |
+
"epoch": 8.64,
|
2275 |
+
"learning_rate": 7.576049487880033e-06,
|
2276 |
+
"loss": 0.0103,
|
2277 |
+
"step": 378
|
2278 |
+
},
|
2279 |
+
{
|
2280 |
+
"epoch": 8.66,
|
2281 |
+
"learning_rate": 7.291024831525961e-06,
|
2282 |
+
"loss": 0.0044,
|
2283 |
+
"step": 379
|
2284 |
+
},
|
2285 |
+
{
|
2286 |
+
"epoch": 8.69,
|
2287 |
+
"learning_rate": 7.011262132981456e-06,
|
2288 |
+
"loss": 0.051,
|
2289 |
+
"step": 380
|
2290 |
+
},
|
2291 |
+
{
|
2292 |
+
"epoch": 8.71,
|
2293 |
+
"learning_rate": 6.7367772709627905e-06,
|
2294 |
+
"loss": 0.0031,
|
2295 |
+
"step": 381
|
2296 |
+
},
|
2297 |
+
{
|
2298 |
+
"epoch": 8.73,
|
2299 |
+
"learning_rate": 6.467585824627887e-06,
|
2300 |
+
"loss": 0.016,
|
2301 |
+
"step": 382
|
2302 |
+
},
|
2303 |
+
{
|
2304 |
+
"epoch": 8.75,
|
2305 |
+
"learning_rate": 6.203703072692013e-06,
|
2306 |
+
"loss": 0.0054,
|
2307 |
+
"step": 383
|
2308 |
+
},
|
2309 |
+
{
|
2310 |
+
"epoch": 8.78,
|
2311 |
+
"learning_rate": 5.945143992560587e-06,
|
2312 |
+
"loss": 0.0042,
|
2313 |
+
"step": 384
|
2314 |
+
},
|
2315 |
+
{
|
2316 |
+
"epoch": 8.8,
|
2317 |
+
"learning_rate": 5.691923259479093e-06,
|
2318 |
+
"loss": 0.0133,
|
2319 |
+
"step": 385
|
2320 |
+
},
|
2321 |
+
{
|
2322 |
+
"epoch": 8.82,
|
2323 |
+
"learning_rate": 5.444055245700208e-06,
|
2324 |
+
"loss": 0.026,
|
2325 |
+
"step": 386
|
2326 |
+
},
|
2327 |
+
{
|
2328 |
+
"epoch": 8.85,
|
2329 |
+
"learning_rate": 5.201554019667965e-06,
|
2330 |
+
"loss": 0.0347,
|
2331 |
+
"step": 387
|
2332 |
+
},
|
2333 |
+
{
|
2334 |
+
"epoch": 8.87,
|
2335 |
+
"learning_rate": 4.964433345219355e-06,
|
2336 |
+
"loss": 0.0498,
|
2337 |
+
"step": 388
|
2338 |
+
},
|
2339 |
+
{
|
2340 |
+
"epoch": 8.89,
|
2341 |
+
"learning_rate": 4.732706680803045e-06,
|
2342 |
+
"loss": 0.0218,
|
2343 |
+
"step": 389
|
2344 |
+
},
|
2345 |
+
{
|
2346 |
+
"epoch": 8.91,
|
2347 |
+
"learning_rate": 4.506387178715565e-06,
|
2348 |
+
"loss": 0.0094,
|
2349 |
+
"step": 390
|
2350 |
+
},
|
2351 |
+
{
|
2352 |
+
"epoch": 8.94,
|
2353 |
+
"learning_rate": 4.285487684354772e-06,
|
2354 |
+
"loss": 0.0798,
|
2355 |
+
"step": 391
|
2356 |
+
},
|
2357 |
+
{
|
2358 |
+
"epoch": 8.96,
|
2359 |
+
"learning_rate": 4.070020735490809e-06,
|
2360 |
+
"loss": 0.0036,
|
2361 |
+
"step": 392
|
2362 |
+
},
|
2363 |
+
{
|
2364 |
+
"epoch": 8.98,
|
2365 |
+
"learning_rate": 3.859998561554434e-06,
|
2366 |
+
"loss": 0.0086,
|
2367 |
+
"step": 393
|
2368 |
+
},
|
2369 |
+
{
|
2370 |
+
"epoch": 9.01,
|
2371 |
+
"learning_rate": 3.655433082942972e-06,
|
2372 |
+
"loss": 0.0673,
|
2373 |
+
"step": 394
|
2374 |
+
},
|
2375 |
+
{
|
2376 |
+
"epoch": 9.03,
|
2377 |
+
"learning_rate": 3.4563359103436886e-06,
|
2378 |
+
"loss": 0.0103,
|
2379 |
+
"step": 395
|
2380 |
+
},
|
2381 |
+
{
|
2382 |
+
"epoch": 9.05,
|
2383 |
+
"learning_rate": 3.262718344074811e-06,
|
2384 |
+
"loss": 0.0038,
|
2385 |
+
"step": 396
|
2386 |
+
},
|
2387 |
+
{
|
2388 |
+
"epoch": 9.07,
|
2389 |
+
"learning_rate": 3.0745913734441355e-06,
|
2390 |
+
"loss": 0.0127,
|
2391 |
+
"step": 397
|
2392 |
+
},
|
2393 |
+
{
|
2394 |
+
"epoch": 9.1,
|
2395 |
+
"learning_rate": 2.891965676125352e-06,
|
2396 |
+
"loss": 0.0093,
|
2397 |
+
"step": 398
|
2398 |
+
},
|
2399 |
+
{
|
2400 |
+
"epoch": 9.12,
|
2401 |
+
"learning_rate": 2.7148516175519277e-06,
|
2402 |
+
"loss": 0.0137,
|
2403 |
+
"step": 399
|
2404 |
+
},
|
2405 |
+
{
|
2406 |
+
"epoch": 9.14,
|
2407 |
+
"learning_rate": 2.5432592503288e-06,
|
2408 |
+
"loss": 0.0027,
|
2409 |
+
"step": 400
|
2410 |
+
},
|
2411 |
+
{
|
2412 |
+
"epoch": 9.17,
|
2413 |
+
"learning_rate": 2.377198313661877e-06,
|
2414 |
+
"loss": 0.0102,
|
2415 |
+
"step": 401
|
2416 |
+
},
|
2417 |
+
{
|
2418 |
+
"epoch": 9.19,
|
2419 |
+
"learning_rate": 2.2166782328051803e-06,
|
2420 |
+
"loss": 0.0051,
|
2421 |
+
"step": 402
|
2422 |
+
},
|
2423 |
+
{
|
2424 |
+
"epoch": 9.21,
|
2425 |
+
"learning_rate": 2.0617081185259512e-06,
|
2426 |
+
"loss": 0.0027,
|
2427 |
+
"step": 403
|
2428 |
+
},
|
2429 |
+
{
|
2430 |
+
"epoch": 9.23,
|
2431 |
+
"learning_rate": 1.912296766587507e-06,
|
2432 |
+
"loss": 0.0074,
|
2433 |
+
"step": 404
|
2434 |
+
},
|
2435 |
+
{
|
2436 |
+
"epoch": 9.26,
|
2437 |
+
"learning_rate": 1.7684526572500416e-06,
|
2438 |
+
"loss": 0.0029,
|
2439 |
+
"step": 405
|
2440 |
+
},
|
2441 |
+
{
|
2442 |
+
"epoch": 9.28,
|
2443 |
+
"learning_rate": 1.6301839547892328e-06,
|
2444 |
+
"loss": 0.0106,
|
2445 |
+
"step": 406
|
2446 |
+
},
|
2447 |
+
{
|
2448 |
+
"epoch": 9.3,
|
2449 |
+
"learning_rate": 1.4974985070329683e-06,
|
2450 |
+
"loss": 0.0243,
|
2451 |
+
"step": 407
|
2452 |
+
},
|
2453 |
+
{
|
2454 |
+
"epoch": 9.33,
|
2455 |
+
"learning_rate": 1.3704038449158573e-06,
|
2456 |
+
"loss": 0.0031,
|
2457 |
+
"step": 408
|
2458 |
+
},
|
2459 |
+
{
|
2460 |
+
"epoch": 9.35,
|
2461 |
+
"learning_rate": 1.2489071820517396e-06,
|
2462 |
+
"loss": 0.0041,
|
2463 |
+
"step": 409
|
2464 |
+
},
|
2465 |
+
{
|
2466 |
+
"epoch": 9.37,
|
2467 |
+
"learning_rate": 1.1330154143243787e-06,
|
2468 |
+
"loss": 0.0096,
|
2469 |
+
"step": 410
|
2470 |
+
},
|
2471 |
+
{
|
2472 |
+
"epoch": 9.39,
|
2473 |
+
"learning_rate": 1.0227351194959545e-06,
|
2474 |
+
"loss": 0.0103,
|
2475 |
+
"step": 411
|
2476 |
+
},
|
2477 |
+
{
|
2478 |
+
"epoch": 9.42,
|
2479 |
+
"learning_rate": 9.180725568338044e-07,
|
2480 |
+
"loss": 0.0069,
|
2481 |
+
"step": 412
|
2482 |
+
},
|
2483 |
+
{
|
2484 |
+
"epoch": 9.44,
|
2485 |
+
"learning_rate": 8.190336667550868e-07,
|
2486 |
+
"loss": 0.0048,
|
2487 |
+
"step": 413
|
2488 |
+
},
|
2489 |
+
{
|
2490 |
+
"epoch": 9.46,
|
2491 |
+
"learning_rate": 7.256240704897166e-07,
|
2492 |
+
"loss": 0.0057,
|
2493 |
+
"step": 414
|
2494 |
+
},
|
2495 |
+
{
|
2496 |
+
"epoch": 9.49,
|
2497 |
+
"learning_rate": 6.378490697611761e-07,
|
2498 |
+
"loss": 0.003,
|
2499 |
+
"step": 415
|
2500 |
+
},
|
2501 |
+
{
|
2502 |
+
"epoch": 9.51,
|
2503 |
+
"learning_rate": 5.55713646485756e-07,
|
2504 |
+
"loss": 0.0067,
|
2505 |
+
"step": 416
|
2506 |
+
},
|
2507 |
+
{
|
2508 |
+
"epoch": 9.53,
|
2509 |
+
"learning_rate": 4.79222462489648e-07,
|
2510 |
+
"loss": 0.0036,
|
2511 |
+
"step": 417
|
2512 |
+
},
|
2513 |
+
{
|
2514 |
+
"epoch": 9.55,
|
2515 |
+
"learning_rate": 4.0837985924448984e-07,
|
2516 |
+
"loss": 0.0055,
|
2517 |
+
"step": 418
|
2518 |
+
},
|
2519 |
+
{
|
2520 |
+
"epoch": 9.58,
|
2521 |
+
"learning_rate": 3.431898576208292e-07,
|
2522 |
+
"loss": 0.0027,
|
2523 |
+
"step": 419
|
2524 |
+
},
|
2525 |
+
{
|
2526 |
+
"epoch": 9.6,
|
2527 |
+
"learning_rate": 2.836561576599839e-07,
|
2528 |
+
"loss": 0.0069,
|
2529 |
+
"step": 420
|
2530 |
+
},
|
2531 |
+
{
|
2532 |
+
"epoch": 9.62,
|
2533 |
+
"learning_rate": 2.2978213836400975e-07,
|
2534 |
+
"loss": 0.0185,
|
2535 |
+
"step": 421
|
2536 |
+
},
|
2537 |
+
{
|
2538 |
+
"epoch": 9.65,
|
2539 |
+
"learning_rate": 1.815708575038988e-07,
|
2540 |
+
"loss": 0.0238,
|
2541 |
+
"step": 422
|
2542 |
+
},
|
2543 |
+
{
|
2544 |
+
"epoch": 9.67,
|
2545 |
+
"learning_rate": 1.3902505144608446e-07,
|
2546 |
+
"loss": 0.012,
|
2547 |
+
"step": 423
|
2548 |
+
},
|
2549 |
+
{
|
2550 |
+
"epoch": 9.69,
|
2551 |
+
"learning_rate": 1.0214713499706597e-07,
|
2552 |
+
"loss": 0.003,
|
2553 |
+
"step": 424
|
2554 |
+
},
|
2555 |
+
{
|
2556 |
+
"epoch": 9.71,
|
2557 |
+
"learning_rate": 7.093920126638454e-08,
|
2558 |
+
"loss": 0.0022,
|
2559 |
+
"step": 425
|
2560 |
+
},
|
2561 |
+
{
|
2562 |
+
"epoch": 9.74,
|
2563 |
+
"learning_rate": 4.54030215478074e-08,
|
2564 |
+
"loss": 0.0037,
|
2565 |
+
"step": 426
|
2566 |
+
},
|
2567 |
+
{
|
2568 |
+
"epoch": 9.76,
|
2569 |
+
"learning_rate": 2.5540045218819253e-08,
|
2570 |
+
"loss": 0.0024,
|
2571 |
+
"step": 427
|
2572 |
+
},
|
2573 |
+
{
|
2574 |
+
"epoch": 9.78,
|
2575 |
+
"learning_rate": 1.1351399658321438e-08,
|
2576 |
+
"loss": 0.0027,
|
2577 |
+
"step": 428
|
2578 |
+
},
|
2579 |
+
{
|
2580 |
+
"epoch": 9.81,
|
2581 |
+
"learning_rate": 2.8378901826831005e-09,
|
2582 |
+
"loss": 0.0033,
|
2583 |
+
"step": 429
|
2584 |
+
},
|
2585 |
+
{
|
2586 |
+
"epoch": 9.83,
|
2587 |
+
"learning_rate": 0.0,
|
2588 |
+
"loss": 0.0051,
|
2589 |
+
"step": 430
|
2590 |
+
},
|
2591 |
+
{
|
2592 |
+
"epoch": 9.83,
|
2593 |
+
"step": 430,
|
2594 |
+
"total_flos": 2.686707530150707e+16,
|
2595 |
+
"train_loss": 0.1627144819580365,
|
2596 |
+
"train_runtime": 335.6804,
|
2597 |
+
"train_samples_per_second": 20.794,
|
2598 |
+
"train_steps_per_second": 1.281
|
2599 |
+
}
|
2600 |
+
],
|
2601 |
+
"logging_steps": 1.0,
|
2602 |
+
"max_steps": 430,
|
2603 |
+
"num_input_tokens_seen": 0,
|
2604 |
+
"num_train_epochs": 10,
|
2605 |
+
"save_steps": 50000,
|
2606 |
+
"total_flos": 2.686707530150707e+16,
|
2607 |
+
"train_batch_size": 4,
|
2608 |
+
"trial_name": null,
|
2609 |
+
"trial_params": null
|
2610 |
+
}
|