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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: 0.1390 |
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- Rewards/chosen: 3.4895 |
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- Rewards/rejected: -9.2522 |
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- Rewards/accuracies: 0.9297 |
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- Rewards/margins: 12.7417 |
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- Logps/rejected: -139.5015 |
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- Logps/chosen: -120.3246 |
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- Logits/rejected: -1.8106 |
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- Logits/chosen: -1.8098 |
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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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| 0.1523 | 0.21 | 100 | 0.1399 | 2.5441 | -8.9516 | 0.9375 | 11.4956 | -137.9985 | -125.0519 | -1.8014 | -1.8101 | |
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| 0.176 | 0.42 | 200 | 0.1358 | 3.3974 | -8.7531 | 0.9375 | 12.1505 | -137.0064 | -120.7853 | -1.8762 | -1.8764 | |
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| 0.1509 | 0.63 | 300 | 0.1403 | 3.3534 | -9.3163 | 0.9336 | 12.6696 | -139.8221 | -121.0054 | -1.7873 | -1.7875 | |
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| 0.2009 | 0.84 | 400 | 0.1390 | 3.4895 | -9.2522 | 0.9297 | 12.7417 | -139.5015 | -120.3246 | -1.8106 | -1.8098 | |
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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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