End of training
Browse files- README.md +23 -2
- all_results.json +6 -6
- eval_results.json +3 -3
- train_results.json +3 -3
- trainer_state.json +12 -12
README.md
CHANGED
@@ -3,6 +3,8 @@ license: mit
|
|
3 |
base_model: microsoft/deberta-v3-base
|
4 |
tags:
|
5 |
- generated_from_trainer
|
|
|
|
|
6 |
metrics:
|
7 |
- precision
|
8 |
- recall
|
@@ -10,7 +12,26 @@ metrics:
|
|
10 |
- accuracy
|
11 |
model-index:
|
12 |
- name: deberta-v3-base-company-names
|
13 |
-
results:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
14 |
---
|
15 |
|
16 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
@@ -18,7 +39,7 @@ should probably proofread and complete it, then remove this comment. -->
|
|
18 |
|
19 |
# deberta-v3-base-company-names
|
20 |
|
21 |
-
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on
|
22 |
It achieves the following results on the evaluation set:
|
23 |
- Loss: 0.0693
|
24 |
- Precision: 0.7740
|
|
|
3 |
base_model: microsoft/deberta-v3-base
|
4 |
tags:
|
5 |
- generated_from_trainer
|
6 |
+
datasets:
|
7 |
+
- nbroad/company_names
|
8 |
metrics:
|
9 |
- precision
|
10 |
- recall
|
|
|
12 |
- accuracy
|
13 |
model-index:
|
14 |
- name: deberta-v3-base-company-names
|
15 |
+
results:
|
16 |
+
- task:
|
17 |
+
name: Token Classification
|
18 |
+
type: token-classification
|
19 |
+
dataset:
|
20 |
+
name: nbroad/company_names
|
21 |
+
type: nbroad/company_names
|
22 |
+
metrics:
|
23 |
+
- name: Precision
|
24 |
+
type: precision
|
25 |
+
value: 0.7739696312364425
|
26 |
+
- name: Recall
|
27 |
+
type: recall
|
28 |
+
value: 0.7962863774326013
|
29 |
+
- name: F1
|
30 |
+
type: f1
|
31 |
+
value: 0.7849694196330357
|
32 |
+
- name: Accuracy
|
33 |
+
type: accuracy
|
34 |
+
value: 0.9769126125154315
|
35 |
---
|
36 |
|
37 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
|
39 |
|
40 |
# deberta-v3-base-company-names
|
41 |
|
42 |
+
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the nbroad/company_names dataset.
|
43 |
It achieves the following results on the evaluation set:
|
44 |
- Loss: 0.0693
|
45 |
- Precision: 0.7740
|
all_results.json
CHANGED
@@ -5,13 +5,13 @@
|
|
5 |
"eval_loss": 0.06933891773223877,
|
6 |
"eval_precision": 0.7739696312364425,
|
7 |
"eval_recall": 0.7962863774326013,
|
8 |
-
"eval_runtime":
|
9 |
"eval_samples": 14160,
|
10 |
-
"eval_samples_per_second":
|
11 |
-
"eval_steps_per_second":
|
12 |
"train_loss": 0.06623676680927928,
|
13 |
-
"train_runtime":
|
14 |
"train_samples": 102018,
|
15 |
-
"train_samples_per_second":
|
16 |
-
"train_steps_per_second":
|
17 |
}
|
|
|
5 |
"eval_loss": 0.06933891773223877,
|
6 |
"eval_precision": 0.7739696312364425,
|
7 |
"eval_recall": 0.7962863774326013,
|
8 |
+
"eval_runtime": 14.3197,
|
9 |
"eval_samples": 14160,
|
10 |
+
"eval_samples_per_second": 988.85,
|
11 |
+
"eval_steps_per_second": 123.606,
|
12 |
"train_loss": 0.06623676680927928,
|
13 |
+
"train_runtime": 577.8703,
|
14 |
"train_samples": 102018,
|
15 |
+
"train_samples_per_second": 529.624,
|
16 |
+
"train_steps_per_second": 11.037
|
17 |
}
|
eval_results.json
CHANGED
@@ -5,8 +5,8 @@
|
|
5 |
"eval_loss": 0.06933891773223877,
|
6 |
"eval_precision": 0.7739696312364425,
|
7 |
"eval_recall": 0.7962863774326013,
|
8 |
-
"eval_runtime":
|
9 |
"eval_samples": 14160,
|
10 |
-
"eval_samples_per_second":
|
11 |
-
"eval_steps_per_second":
|
12 |
}
|
|
|
5 |
"eval_loss": 0.06933891773223877,
|
6 |
"eval_precision": 0.7739696312364425,
|
7 |
"eval_recall": 0.7962863774326013,
|
8 |
+
"eval_runtime": 14.3197,
|
9 |
"eval_samples": 14160,
|
10 |
+
"eval_samples_per_second": 988.85,
|
11 |
+
"eval_steps_per_second": 123.606
|
12 |
}
|
train_results.json
CHANGED
@@ -1,8 +1,8 @@
|
|
1 |
{
|
2 |
"epoch": 3.0,
|
3 |
"train_loss": 0.06623676680927928,
|
4 |
-
"train_runtime":
|
5 |
"train_samples": 102018,
|
6 |
-
"train_samples_per_second":
|
7 |
-
"train_steps_per_second":
|
8 |
}
|
|
|
1 |
{
|
2 |
"epoch": 3.0,
|
3 |
"train_loss": 0.06623676680927928,
|
4 |
+
"train_runtime": 577.8703,
|
5 |
"train_samples": 102018,
|
6 |
+
"train_samples_per_second": 529.624,
|
7 |
+
"train_steps_per_second": 11.037
|
8 |
}
|
trainer_state.json
CHANGED
@@ -1287,9 +1287,9 @@
|
|
1287 |
"eval_loss": 0.0664275586605072,
|
1288 |
"eval_precision": 0.7416196481911715,
|
1289 |
"eval_recall": 0.7978932333511873,
|
1290 |
-
"eval_runtime":
|
1291 |
-
"eval_samples_per_second":
|
1292 |
-
"eval_steps_per_second":
|
1293 |
"step": 2126
|
1294 |
},
|
1295 |
{
|
@@ -2577,9 +2577,9 @@
|
|
2577 |
"eval_loss": 0.06523581594228745,
|
2578 |
"eval_precision": 0.7725130890052356,
|
2579 |
"eval_recall": 0.7903053026245314,
|
2580 |
-
"eval_runtime":
|
2581 |
-
"eval_samples_per_second":
|
2582 |
-
"eval_steps_per_second":
|
2583 |
"step": 4252
|
2584 |
},
|
2585 |
{
|
@@ -3861,9 +3861,9 @@
|
|
3861 |
"eval_loss": 0.06933891773223877,
|
3862 |
"eval_precision": 0.7739696312364425,
|
3863 |
"eval_recall": 0.7962863774326013,
|
3864 |
-
"eval_runtime":
|
3865 |
-
"eval_samples_per_second":
|
3866 |
-
"eval_steps_per_second":
|
3867 |
"step": 6378
|
3868 |
},
|
3869 |
{
|
@@ -3871,9 +3871,9 @@
|
|
3871 |
"step": 6378,
|
3872 |
"total_flos": 1.2518895383371872e+16,
|
3873 |
"train_loss": 0.06623676680927928,
|
3874 |
-
"train_runtime":
|
3875 |
-
"train_samples_per_second":
|
3876 |
-
"train_steps_per_second":
|
3877 |
}
|
3878 |
],
|
3879 |
"logging_steps": 10,
|
|
|
1287 |
"eval_loss": 0.0664275586605072,
|
1288 |
"eval_precision": 0.7416196481911715,
|
1289 |
"eval_recall": 0.7978932333511873,
|
1290 |
+
"eval_runtime": 16.3951,
|
1291 |
+
"eval_samples_per_second": 863.673,
|
1292 |
+
"eval_steps_per_second": 107.959,
|
1293 |
"step": 2126
|
1294 |
},
|
1295 |
{
|
|
|
2577 |
"eval_loss": 0.06523581594228745,
|
2578 |
"eval_precision": 0.7725130890052356,
|
2579 |
"eval_recall": 0.7903053026245314,
|
2580 |
+
"eval_runtime": 16.6261,
|
2581 |
+
"eval_samples_per_second": 851.671,
|
2582 |
+
"eval_steps_per_second": 106.459,
|
2583 |
"step": 4252
|
2584 |
},
|
2585 |
{
|
|
|
3861 |
"eval_loss": 0.06933891773223877,
|
3862 |
"eval_precision": 0.7739696312364425,
|
3863 |
"eval_recall": 0.7962863774326013,
|
3864 |
+
"eval_runtime": 16.4386,
|
3865 |
+
"eval_samples_per_second": 861.385,
|
3866 |
+
"eval_steps_per_second": 107.673,
|
3867 |
"step": 6378
|
3868 |
},
|
3869 |
{
|
|
|
3871 |
"step": 6378,
|
3872 |
"total_flos": 1.2518895383371872e+16,
|
3873 |
"train_loss": 0.06623676680927928,
|
3874 |
+
"train_runtime": 577.8703,
|
3875 |
+
"train_samples_per_second": 529.624,
|
3876 |
+
"train_steps_per_second": 11.037
|
3877 |
}
|
3878 |
],
|
3879 |
"logging_steps": 10,
|