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--- |
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license: mit |
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base_model: openai-community/gpt2 |
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tags: |
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- trl |
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- dpo |
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- generated_from_trainer |
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model-index: |
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- name: gpt2-dpo-from_base_gpt2 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# gpt2-dpo-from_base_gpt2 |
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This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co./openai-community/gpt2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6406 |
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- Rewards/chosen: 1.1312 |
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- Rewards/rejected: 0.9208 |
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- Rewards/accuracies: 0.6373 |
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- Rewards/margins: 0.2103 |
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- Logps/rejected: -429.5498 |
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- Logps/chosen: -508.5024 |
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- Logits/rejected: -96.1598 |
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- Logits/chosen: -94.9073 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-07 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.2 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 0.6679 | 0.9993 | 668 | 0.6728 | 0.2747 | 0.2209 | 0.625 | 0.0538 | -436.5490 | -517.0669 | -96.0258 | -94.8005 | |
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| 0.6697 | 2.0 | 1337 | 0.6545 | 0.6507 | 0.5283 | 0.6295 | 0.1224 | -433.4745 | -513.3065 | -96.0560 | -94.8147 | |
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| 0.6516 | 2.9993 | 2005 | 0.6467 | 0.8424 | 0.6867 | 0.6336 | 0.1557 | -431.8912 | -511.3903 | -96.1361 | -94.8919 | |
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| 0.6264 | 4.0 | 2674 | 0.6436 | 0.9803 | 0.7989 | 0.6336 | 0.1814 | -430.7686 | -510.0109 | -96.1278 | -94.8762 | |
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| 0.6114 | 4.9993 | 3342 | 0.6420 | 1.0453 | 0.8518 | 0.6377 | 0.1935 | -430.2403 | -509.3612 | -96.1435 | -94.8917 | |
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| 0.6016 | 6.0 | 4011 | 0.6412 | 1.0870 | 0.8859 | 0.6377 | 0.2011 | -429.8991 | -508.9442 | -96.1471 | -94.8941 | |
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| 0.6115 | 6.9993 | 4679 | 0.6408 | 1.1137 | 0.9071 | 0.6384 | 0.2066 | -429.6871 | -508.6768 | -96.1587 | -94.9064 | |
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| 0.6079 | 8.0 | 5348 | 0.6406 | 1.1274 | 0.9178 | 0.6388 | 0.2096 | -429.5802 | -508.5403 | -96.1573 | -94.9046 | |
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| 0.6066 | 8.9993 | 6016 | 0.6406 | 1.1310 | 0.9207 | 0.6373 | 0.2103 | -429.5507 | -508.5036 | -96.1593 | -94.9068 | |
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| 0.5968 | 9.9925 | 6680 | 0.6406 | 1.1312 | 0.9208 | 0.6373 | 0.2103 | -429.5498 | -508.5024 | -96.1598 | -94.9073 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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