chchen commited on
Commit
510524c
1 Parent(s): 0fbe69d

Model save

Browse files
Files changed (2) hide show
  1. README.md +77 -0
  2. trainer_log.jsonl +28 -0
README.md ADDED
@@ -0,0 +1,77 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: gemma
3
+ library_name: peft
4
+ tags:
5
+ - trl
6
+ - dpo
7
+ - llama-factory
8
+ - generated_from_trainer
9
+ base_model: google/gemma-7b-it
10
+ model-index:
11
+ - name: Gemma-7B-It-ORPO-SALT-HALF
12
+ results: []
13
+ ---
14
+
15
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
16
+ should probably proofread and complete it, then remove this comment. -->
17
+
18
+ # Gemma-7B-It-ORPO-SALT-HALF
19
+
20
+ This model is a fine-tuned version of [google/gemma-7b-it](https://huggingface.co/google/gemma-7b-it) on the None dataset.
21
+ It achieves the following results on the evaluation set:
22
+ - Loss: 1.3159
23
+ - Rewards/chosen: -0.1249
24
+ - Rewards/rejected: -0.1471
25
+ - Rewards/accuracies: 0.5619
26
+ - Rewards/margins: 0.0222
27
+ - Logps/rejected: -1.4709
28
+ - Logps/chosen: -1.2488
29
+ - Logits/rejected: 253.8645
30
+ - Logits/chosen: 253.5439
31
+ - Sft Loss: 1.2488
32
+ - Odds Ratio Loss: 0.6713
33
+
34
+ ## Model description
35
+
36
+ More information needed
37
+
38
+ ## Intended uses & limitations
39
+
40
+ More information needed
41
+
42
+ ## Training and evaluation data
43
+
44
+ More information needed
45
+
46
+ ## Training procedure
47
+
48
+ ### Training hyperparameters
49
+
50
+ The following hyperparameters were used during training:
51
+ - learning_rate: 5e-06
52
+ - train_batch_size: 2
53
+ - eval_batch_size: 2
54
+ - seed: 42
55
+ - gradient_accumulation_steps: 8
56
+ - total_train_batch_size: 16
57
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
58
+ - lr_scheduler_type: cosine
59
+ - lr_scheduler_warmup_steps: 0.1
60
+ - num_epochs: 3.0
61
+
62
+ ### Training results
63
+
64
+ | Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Sft Loss | Odds Ratio Loss |
65
+ |:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:|
66
+ | 1.422 | 0.8467 | 500 | 1.3896 | -0.1322 | -0.1546 | 0.5752 | 0.0224 | -1.5459 | -1.3222 | 250.5634 | 250.2739 | 1.3222 | 0.6733 |
67
+ | 1.3103 | 1.6935 | 1000 | 1.3313 | -0.1264 | -0.1489 | 0.5695 | 0.0224 | -1.4886 | -1.2642 | 253.1350 | 252.8147 | 1.2642 | 0.6718 |
68
+ | 1.2057 | 2.5402 | 1500 | 1.3159 | -0.1249 | -0.1471 | 0.5619 | 0.0222 | -1.4709 | -1.2488 | 253.8645 | 253.5439 | 1.2488 | 0.6713 |
69
+
70
+
71
+ ### Framework versions
72
+
73
+ - PEFT 0.10.0
74
+ - Transformers 4.40.1
75
+ - Pytorch 2.3.0
76
+ - Datasets 2.19.0
77
+ - Tokenizers 0.19.1
trainer_log.jsonl CHANGED
@@ -151,3 +151,31 @@
151
  {"current_steps": 1490, "total_steps": 1770, "loss": 1.2608, "accuracy": 0.574999988079071, "learning_rate": 3.024615823368371e-07, "epoch": 2.523285351397121, "percentage": 84.18, "elapsed_time": "5:27:34", "remaining_time": "1:01:33"}
152
  {"current_steps": 1500, "total_steps": 1770, "loss": 1.2057, "accuracy": 0.5625, "learning_rate": 2.8165102503600716e-07, "epoch": 2.5402201524132093, "percentage": 84.75, "elapsed_time": "5:29:42", "remaining_time": "0:59:20"}
153
  {"current_steps": 1500, "total_steps": 1770, "eval_loss": 1.3159173727035522, "epoch": 2.5402201524132093, "percentage": 84.75, "elapsed_time": "5:33:24", "remaining_time": "1:00:00"}
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
151
  {"current_steps": 1490, "total_steps": 1770, "loss": 1.2608, "accuracy": 0.574999988079071, "learning_rate": 3.024615823368371e-07, "epoch": 2.523285351397121, "percentage": 84.18, "elapsed_time": "5:27:34", "remaining_time": "1:01:33"}
152
  {"current_steps": 1500, "total_steps": 1770, "loss": 1.2057, "accuracy": 0.5625, "learning_rate": 2.8165102503600716e-07, "epoch": 2.5402201524132093, "percentage": 84.75, "elapsed_time": "5:29:42", "remaining_time": "0:59:20"}
153
  {"current_steps": 1500, "total_steps": 1770, "eval_loss": 1.3159173727035522, "epoch": 2.5402201524132093, "percentage": 84.75, "elapsed_time": "5:33:24", "remaining_time": "1:00:00"}
154
+ {"current_steps": 1510, "total_steps": 1770, "loss": 1.3937, "accuracy": 0.543749988079071, "learning_rate": 2.615393769259039e-07, "epoch": 2.557154953429297, "percentage": 85.31, "elapsed_time": "5:35:40", "remaining_time": "0:57:47"}
155
+ {"current_steps": 1520, "total_steps": 1770, "loss": 1.2334, "accuracy": 0.543749988079071, "learning_rate": 2.421329743475917e-07, "epoch": 2.574089754445385, "percentage": 85.88, "elapsed_time": "5:37:46", "remaining_time": "0:55:33"}
156
+ {"current_steps": 1530, "total_steps": 1770, "loss": 1.3281, "accuracy": 0.5375000238418579, "learning_rate": 2.234379314486973e-07, "epoch": 2.5910245554614733, "percentage": 86.44, "elapsed_time": "5:39:57", "remaining_time": "0:53:19"}
157
+ {"current_steps": 1540, "total_steps": 1770, "loss": 1.2628, "accuracy": 0.6000000238418579, "learning_rate": 2.0546013825709783e-07, "epoch": 2.6079593564775614, "percentage": 87.01, "elapsed_time": "5:42:10", "remaining_time": "0:51:06"}
158
+ {"current_steps": 1550, "total_steps": 1770, "loss": 1.1414, "accuracy": 0.6187499761581421, "learning_rate": 1.88205258825217e-07, "epoch": 2.6248941574936495, "percentage": 87.57, "elapsed_time": "5:44:24", "remaining_time": "0:48:53"}
159
+ {"current_steps": 1560, "total_steps": 1770, "loss": 1.2452, "accuracy": 0.550000011920929, "learning_rate": 1.7167872944552245e-07, "epoch": 2.6418289585097376, "percentage": 88.14, "elapsed_time": "5:46:29", "remaining_time": "0:46:38"}
160
+ {"current_steps": 1570, "total_steps": 1770, "loss": 1.2281, "accuracy": 0.5, "learning_rate": 1.5588575693777142e-07, "epoch": 2.6587637595258258, "percentage": 88.7, "elapsed_time": "5:48:43", "remaining_time": "0:44:25"}
161
+ {"current_steps": 1580, "total_steps": 1770, "loss": 1.3435, "accuracy": 0.5062500238418579, "learning_rate": 1.4083131700856428e-07, "epoch": 2.675698560541914, "percentage": 89.27, "elapsed_time": "5:50:58", "remaining_time": "0:42:12"}
162
+ {"current_steps": 1590, "total_steps": 1770, "loss": 1.2371, "accuracy": 0.606249988079071, "learning_rate": 1.2652015268370315e-07, "epoch": 2.6926333615580016, "percentage": 89.83, "elapsed_time": "5:53:06", "remaining_time": "0:39:58"}
163
+ {"current_steps": 1600, "total_steps": 1770, "loss": 1.3777, "accuracy": 0.581250011920929, "learning_rate": 1.1295677281386502e-07, "epoch": 2.7095681625740897, "percentage": 90.4, "elapsed_time": "5:55:21", "remaining_time": "0:37:45"}
164
+ {"current_steps": 1610, "total_steps": 1770, "loss": 1.323, "accuracy": 0.574999988079071, "learning_rate": 1.0014545065404973e-07, "epoch": 2.726502963590178, "percentage": 90.96, "elapsed_time": "5:57:31", "remaining_time": "0:35:31"}
165
+ {"current_steps": 1620, "total_steps": 1770, "loss": 1.285, "accuracy": 0.574999988079071, "learning_rate": 8.809022251725502e-08, "epoch": 2.743437764606266, "percentage": 91.53, "elapsed_time": "5:59:42", "remaining_time": "0:33:18"}
166
+ {"current_steps": 1630, "total_steps": 1770, "loss": 1.3117, "accuracy": 0.5375000238418579, "learning_rate": 7.679488650280509e-08, "epoch": 2.7603725656223537, "percentage": 92.09, "elapsed_time": "6:01:57", "remaining_time": "0:31:05"}
167
+ {"current_steps": 1640, "total_steps": 1770, "loss": 1.2449, "accuracy": 0.5375000238418579, "learning_rate": 6.626300129972563e-08, "epoch": 2.777307366638442, "percentage": 92.66, "elapsed_time": "6:03:59", "remaining_time": "0:28:51"}
168
+ {"current_steps": 1650, "total_steps": 1770, "loss": 1.2878, "accuracy": 0.6000000238418579, "learning_rate": 5.649788506555065e-08, "epoch": 2.79424216765453, "percentage": 93.22, "elapsed_time": "6:06:05", "remaining_time": "0:26:37"}
169
+ {"current_steps": 1660, "total_steps": 1770, "loss": 1.2631, "accuracy": 0.581250011920929, "learning_rate": 4.7502614380908474e-08, "epoch": 2.811176968670618, "percentage": 93.79, "elapsed_time": "6:08:16", "remaining_time": "0:24:24"}
170
+ {"current_steps": 1670, "total_steps": 1770, "loss": 1.2531, "accuracy": 0.550000011920929, "learning_rate": 3.9280023280222066e-08, "epoch": 2.828111769686706, "percentage": 94.35, "elapsed_time": "6:10:25", "remaining_time": "0:22:10"}
171
+ {"current_steps": 1680, "total_steps": 1770, "loss": 1.288, "accuracy": 0.5562499761581421, "learning_rate": 3.1832702358818855e-08, "epoch": 2.8450465707027943, "percentage": 94.92, "elapsed_time": "6:12:45", "remaining_time": "0:19:58"}
172
+ {"current_steps": 1690, "total_steps": 1770, "loss": 1.2743, "accuracy": 0.5687500238418579, "learning_rate": 2.5162997956746647e-08, "epoch": 2.8619813717188824, "percentage": 95.48, "elapsed_time": "6:15:05", "remaining_time": "0:17:45"}
173
+ {"current_steps": 1700, "total_steps": 1770, "loss": 1.3412, "accuracy": 0.5874999761581421, "learning_rate": 1.9273011419536914e-08, "epoch": 2.8789161727349706, "percentage": 96.05, "elapsed_time": "6:17:00", "remaining_time": "0:15:31"}
174
+ {"current_steps": 1710, "total_steps": 1770, "loss": 1.2679, "accuracy": 0.5562499761581421, "learning_rate": 1.4164598436159083e-08, "epoch": 2.8958509737510583, "percentage": 96.61, "elapsed_time": "6:19:03", "remaining_time": "0:13:18"}
175
+ {"current_steps": 1720, "total_steps": 1770, "loss": 1.213, "accuracy": 0.606249988079071, "learning_rate": 9.839368454371556e-09, "epoch": 2.9127857747671464, "percentage": 97.18, "elapsed_time": "6:21:14", "remaining_time": "0:11:04"}
176
+ {"current_steps": 1730, "total_steps": 1770, "loss": 1.2129, "accuracy": 0.5874999761581421, "learning_rate": 6.298684173650649e-09, "epoch": 2.9297205757832345, "percentage": 97.74, "elapsed_time": "6:23:20", "remaining_time": "0:08:51"}
177
+ {"current_steps": 1740, "total_steps": 1770, "loss": 1.2883, "accuracy": 0.5625, "learning_rate": 3.543661115860686e-09, "epoch": 2.9466553767993227, "percentage": 98.31, "elapsed_time": "6:25:17", "remaining_time": "0:06:38"}
178
+ {"current_steps": 1750, "total_steps": 1770, "loss": 1.249, "accuracy": 0.574999988079071, "learning_rate": 1.575167273800693e-09, "epoch": 2.963590177815411, "percentage": 98.87, "elapsed_time": "6:27:15", "remaining_time": "0:04:25"}
179
+ {"current_steps": 1760, "total_steps": 1770, "loss": 1.3394, "accuracy": 0.574999988079071, "learning_rate": 3.9382283773564676e-10, "epoch": 2.9805249788314985, "percentage": 99.44, "elapsed_time": "6:29:28", "remaining_time": "0:02:12"}
180
+ {"current_steps": 1770, "total_steps": 1770, "loss": 1.3966, "accuracy": 0.606249988079071, "learning_rate": 0.0, "epoch": 2.9974597798475866, "percentage": 100.0, "elapsed_time": "6:31:33", "remaining_time": "0:00:00"}
181
+ {"current_steps": 1770, "total_steps": 1770, "epoch": 2.9974597798475866, "percentage": 100.0, "elapsed_time": "6:31:33", "remaining_time": "0:00:00"}