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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: 0.1695 |
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- Rewards/chosen: 8.1916 |
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- Rewards/rejected: -16.5277 |
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- Rewards/accuracies: 0.9297 |
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- Rewards/margins: 24.7193 |
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- Logps/rejected: -126.2961 |
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- Logps/chosen: -121.3891 |
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- Logits/rejected: -1.8336 |
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- Logits/chosen: -1.8336 |
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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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| 0.1474 | 0.21 | 100 | 0.1325 | 6.8739 | -14.1333 | 0.9297 | 21.0072 | -121.5073 | -124.0244 | -1.7724 | -1.7834 | |
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| 0.2092 | 0.42 | 200 | 0.1567 | 8.4112 | -15.0418 | 0.9336 | 23.4530 | -123.3244 | -120.9499 | -1.8442 | -1.8477 | |
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| 0.1925 | 0.63 | 300 | 0.1715 | 7.7458 | -16.7009 | 0.9258 | 24.4467 | -126.6425 | -122.2807 | -1.8047 | -1.8054 | |
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| 0.2762 | 0.84 | 400 | 0.1695 | 8.1916 | -16.5277 | 0.9297 | 24.7193 | -126.2961 | -121.3891 | -1.8336 | -1.8336 | |
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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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