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--- |
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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: zephyr-7b-dpo-full |
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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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# zephyr-7b-dpo-full |
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This model was trained from scratch on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5261 |
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- Rewards/chosen: -2.4591 |
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- Rewards/rejected: -3.9221 |
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- Rewards/accuracies: 0.7773 |
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- Rewards/margins: 1.4631 |
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- Logps/rejected: -703.8400 |
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- Logps/chosen: -549.4910 |
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- Logits/rejected: 0.0289 |
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- Logits/chosen: 0.0663 |
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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-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 2 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 64 |
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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: 0.1 |
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- num_epochs: 2 |
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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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| 0.6201 | 0.21 | 100 | 0.6253 | -0.2753 | -0.6662 | 0.7031 | 0.3909 | -378.2405 | -331.1124 | 0.4172 | 0.3706 | |
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| 0.5547 | 0.42 | 200 | 0.5549 | -0.6988 | -1.4726 | 0.7656 | 0.7738 | -458.8863 | -373.4661 | 0.4261 | 0.3909 | |
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| 0.5343 | 0.63 | 300 | 0.5316 | -0.8044 | -1.6474 | 0.7656 | 0.8430 | -476.3628 | -384.0199 | 0.2851 | 0.2449 | |
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| 0.5323 | 0.84 | 400 | 0.5211 | -0.9068 | -1.8283 | 0.7812 | 0.9216 | -494.4600 | -394.2621 | 0.2834 | 0.2514 | |
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| 0.352 | 1.05 | 500 | 0.5258 | -1.9533 | -3.4166 | 0.7969 | 1.4634 | -653.2899 | -498.9117 | -0.0846 | -0.0654 | |
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| 0.3342 | 1.26 | 600 | 0.5268 | -2.3123 | -3.7246 | 0.7930 | 1.4124 | -684.0857 | -534.8101 | 0.1128 | 0.1344 | |
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| 0.337 | 1.47 | 700 | 0.5290 | -2.3753 | -3.8837 | 0.7773 | 1.5084 | -699.9910 | -541.1116 | 0.0099 | 0.0414 | |
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| 0.3398 | 1.67 | 800 | 0.5297 | -2.5097 | -4.0133 | 0.7734 | 1.5036 | -712.9506 | -554.5546 | 0.0381 | 0.0750 | |
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| 0.307 | 1.88 | 900 | 0.5261 | -2.4591 | -3.9221 | 0.7773 | 1.4631 | -703.8400 | -549.4910 | 0.0289 | 0.0663 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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