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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: 0.4913 |
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- Rewards/chosen: -0.8372 |
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- Rewards/rejected: -1.8838 |
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- Rewards/accuracies: 0.7852 |
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- Rewards/margins: 1.0466 |
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- Logps/rejected: -476.1451 |
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- Logps/chosen: -365.3529 |
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- Logits/rejected: -0.9850 |
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- Logits/chosen: -1.0730 |
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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: 5e-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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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 2 |
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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: 1 |
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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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| 0.5671 | 0.21 | 100 | 0.5699 | -0.3533 | -0.8899 | 0.7305 | 0.5366 | -376.7557 | -316.9664 | -1.8571 | -1.8679 | |
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| 0.5413 | 0.42 | 200 | 0.5254 | -0.6740 | -1.4486 | 0.7266 | 0.7745 | -432.6194 | -349.0378 | -1.8679 | -1.9017 | |
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| 0.4829 | 0.63 | 300 | 0.4956 | -0.8661 | -1.8953 | 0.7812 | 1.0292 | -477.2877 | -368.2400 | -1.1994 | -1.2566 | |
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| 0.4981 | 0.84 | 400 | 0.4913 | -0.8372 | -1.8838 | 0.7852 | 1.0466 | -476.1451 | -365.3529 | -0.9850 | -1.0730 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.1.2+cu118 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
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