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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: 1.8652 |
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- Rewards/chosen: 125.1359 |
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- Rewards/rejected: -204.8868 |
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- Rewards/accuracies: 0.9141 |
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- Rewards/margins: 330.0227 |
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- Logps/rejected: -113.7294 |
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- Logps/chosen: -125.2587 |
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- Logits/rejected: -1.8708 |
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- Logits/chosen: -1.8725 |
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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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| 1.1504 | 0.21 | 100 | 0.9784 | 103.9547 | -116.3378 | 0.9102 | 220.2925 | -104.8745 | -127.3768 | -1.6942 | -1.7242 | |
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| 2.8553 | 0.42 | 200 | 1.8849 | 118.2614 | -180.4101 | 0.9102 | 298.6714 | -111.2817 | -125.9461 | -1.8462 | -1.8519 | |
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| 2.2897 | 0.63 | 300 | 2.1029 | 127.9046 | -196.9116 | 0.9141 | 324.8163 | -112.9319 | -124.9818 | -1.8642 | -1.8683 | |
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| 2.2714 | 0.84 | 400 | 1.8652 | 125.1359 | -204.8868 | 0.9141 | 330.0227 | -113.7294 | -125.2587 | -1.8708 | -1.8725 | |
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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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