mNLP-project
/

gpt2-dpo

@@ -6,26 +6,26 @@ tags:
 - dpo
 - generated_from_trainer
 model-index:
-- name: gpt2-dpo-with-cosine-lr-scheduler
   results: []
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
-# gpt2-dpo-with-cosine-lr-scheduler
 This model is a fine-tuned version of [mNLP-project/gpt2-finetuned](https://huggingface.co/mNLP-project/gpt2-finetuned) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 1.1168
-- Rewards/chosen: 3.8849
-- Rewards/rejected: 3.2031
-- Rewards/accuracies: 0.5892
-- Rewards/margins: 0.6818
-- Logps/rejected: -761.2470
-- Logps/chosen: -910.5992
-- Logits/rejected: -36.5651
-- Logits/chosen: -30.3810
 ## Model description
@@ -44,31 +44,31 @@ More information needed
 ### Training hyperparameters
 The following hyperparameters were used during training:
-- learning_rate: 1e-05
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 16
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine
-- lr_scheduler_warmup_ratio: 0.1
 - num_epochs: 10
 ### Training results
-| Training Loss | Epoch | Step  | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
-|:-------------:|:-----:|:-----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
-| 0.9846        | 1.0   | 1337  | 1.1168          | 3.8849         | 3.2031           | 0.5892             | 0.6818          | -761.2470      | -910.5992    | -36.5651        | -30.3810      |
-| 0.6025        | 2.0   | 2674  | 1.1405          | 5.0060         | 4.0992           | 0.6175             | 0.9068          | -752.2864      | -899.3887    | -35.0528        | -28.9839      |
-| 0.2464        | 3.0   | 4011  | 1.1202          | 4.6754         | 3.6835           | 0.6160             | 0.9919          | -756.4427      | -902.6943    | -39.6513        | -33.3219      |
-| 0.1182        | 4.0   | 5348  | 1.3054          | 7.3114         | 5.8367           | 0.6131             | 1.4747          | -734.9108      | -876.3349    | -35.1974        | -28.6005      |
-| 0.0669        | 5.0   | 6685  | 1.3846          | 6.5378         | 5.0738           | 0.6093             | 1.4640          | -742.5399      | -884.0710    | -39.0355        | -31.8814      |
-| 0.0226        | 6.0   | 8022  | 1.4662          | 6.2901         | 4.6812           | 0.6052             | 1.6089          | -746.4659      | -886.5475    | -40.3811        | -32.9593      |
-| 0.0128        | 7.0   | 9359  | 1.5557          | 5.8081         | 4.1554           | 0.6108             | 1.6527          | -751.7241      | -891.3676    | -39.1744        | -31.2704      |
-| 0.019         | 8.0   | 10696 | 1.6676          | 5.5428         | 3.8458           | 0.6011             | 1.6970          | -754.8205      | -894.0207    | -40.5161        | -32.4700      |
-| 0.0101        | 9.0   | 12033 | 1.7100          | 5.5531         | 3.8215           | 0.6022             | 1.7315          | -755.0627      | -893.9178    | -40.7171        | -32.5929      |
-| 0.0053        | 10.0  | 13370 | 1.7177          | 5.4221         | 3.7030           | 0.6000             | 1.7191          | -756.2481      | -895.2274    | -40.8064        | -32.6689      |
 ### Framework versions

 - dpo
 - generated_from_trainer
 model-index:
+- name: gpt2-dpo
   results: []
 ---
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
+# gpt2-dpo
 This model is a fine-tuned version of [mNLP-project/gpt2-finetuned](https://huggingface.co/mNLP-project/gpt2-finetuned) on the None dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.6350
+- Rewards/chosen: 1.6222
+- Rewards/rejected: 1.3204
+- Rewards/accuracies: 0.6496
+- Rewards/margins: 0.3018
+- Logps/rejected: -780.0735
+- Logps/chosen: -933.2262
+- Logits/rejected: -34.5449
+- Logits/chosen: -28.7838
 ## Model description
 ### Training hyperparameters
 The following hyperparameters were used during training:
+- learning_rate: 1e-06
 - train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.2
 - num_epochs: 10
 ### Training results
+| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.6286        | 0.9993 | 668  | 0.6350          | 1.6222         | 1.3204           | 0.6496             | 0.3018          | -780.0735      | -933.2262    | -34.5449        | -28.7838      |
+| 0.6387        | 2.0    | 1337 | 0.6662          | 1.8546         | 1.5416           | 0.6302             | 0.3130          | -777.8622      | -930.9024    | -34.5110        | -28.7424      |
+| 0.5643        | 2.9993 | 2005 | 0.6635          | 2.0534         | 1.6918           | 0.6396             | 0.3616          | -776.3599      | -928.9147    | -34.5066        | -28.7168      |
+| 0.4487        | 4.0    | 2674 | 0.6677          | 2.2748         | 1.8809           | 0.6451             | 0.3940          | -774.4694      | -926.7002    | -34.1409        | -28.2530      |
+| 0.3831        | 4.9993 | 3342 | 0.6783          | 2.4765         | 2.0527           | 0.6418             | 0.4238          | -772.7513      | -924.6838    | -34.0051        | -28.0668      |
+| 0.352         | 6.0    | 4011 | 0.6782          | 2.4441         | 2.0097           | 0.6440             | 0.4344          | -773.1808      | -925.0074    | -34.0868        | -28.1418      |
+| 0.3189        | 6.9993 | 4679 | 0.6840          | 2.2310         | 1.8303           | 0.6343             | 0.4008          | -774.9752      | -927.1384    | -33.9525        | -27.9466      |
+| 0.3006        | 8.0    | 5348 | 0.6882          | 2.4339         | 1.9918           | 0.6388             | 0.4422          | -773.3604      | -925.1093    | -33.7716        | -27.7551      |
+| 0.3152        | 8.9993 | 6016 | 0.6891          | 2.4920         | 2.0457           | 0.6407             | 0.4462          | -772.8206      | -924.5289    | -33.6753        | -27.6463      |
+| 0.2752        | 9.9925 | 6680 | 0.6892          | 2.4562         | 2.0151           | 0.6410             | 0.4411          | -773.1274      | -924.8871    | -33.6818        | -27.6538      |
 ### Framework versions

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