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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: 0.4801 |
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- Rewards/chosen: -0.7670 |
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- Rewards/rejected: -1.9120 |
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- Rewards/accuracies: 0.7617 |
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- Rewards/margins: 1.1450 |
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- Logps/rejected: -508.7245 |
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- Logps/chosen: -388.4799 |
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- Logits/rejected: 0.7285 |
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- Logits/chosen: 0.2273 |
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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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| 0.539 | 0.21 | 100 | 0.5452 | -0.5988 | -1.3188 | 0.7422 | 0.7200 | -449.4053 | -371.6547 | -0.7240 | -0.8812 | |
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| 0.5294 | 0.42 | 200 | 0.5000 | -0.6654 | -1.5376 | 0.7617 | 0.8722 | -471.2849 | -378.3161 | 0.8080 | 0.4502 | |
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| 0.4704 | 0.63 | 300 | 0.4878 | -0.8441 | -1.9900 | 0.7539 | 1.1459 | -516.5240 | -396.1895 | 0.8998 | 0.3977 | |
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| 0.4856 | 0.84 | 400 | 0.4801 | -0.7670 | -1.9120 | 0.7617 | 1.1450 | -508.7245 | -388.4799 | 0.7285 | 0.2273 | |
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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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