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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: 1.1360 |
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- Rewards/chosen: -0.1815 |
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- Rewards/rejected: 0.2981 |
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- Rewards/accuracies: 0.4102 |
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- Rewards/margins: -0.4796 |
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- Logps/rejected: -515.4065 |
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- Logps/chosen: -392.2896 |
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- Logits/rejected: -4.7596 |
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- Logits/chosen: -4.5397 |
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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-08 |
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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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| 0.2984 | 0.26 | 100 | 0.9403 | -0.0277 | 0.3050 | 0.4062 | -0.3328 | -515.3372 | -390.7516 | -4.7620 | -4.5507 | |
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| 0.2338 | 0.51 | 200 | 1.0997 | -0.0605 | 0.4142 | 0.3867 | -0.4747 | -514.2458 | -391.0792 | -4.7584 | -4.5386 | |
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| 0.2158 | 0.77 | 300 | 1.1360 | -0.1815 | 0.2981 | 0.4102 | -0.4796 | -515.4065 | -392.2896 | -4.7596 | -4.5397 | |
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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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