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--- |
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license: apache-2.0 |
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base_model: alignment-handbook/zephyr-7b-sft-full |
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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-UC-0 |
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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-UC-0 |
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This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co./alignment-handbook/zephyr-7b-sft-full) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1374 |
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- Rewards/chosen: -4.8195 |
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- Rewards/rejected: -11.6393 |
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- Rewards/accuracies: 0.8670 |
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- Rewards/margins: 6.8198 |
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- Logps/rejected: -263.2084 |
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- Logps/chosen: -230.3513 |
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- Logits/rejected: -2.6736 |
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- Logits/chosen: -2.7815 |
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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: 4 |
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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: 4 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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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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| 0.1537 | 0.62 | 500 | 0.1480 | -3.7578 | -9.9780 | 0.8564 | 6.2202 | -246.5951 | -219.7342 | -2.7077 | -2.7809 | |
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### Framework versions |
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- Transformers 4.36.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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