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--- |
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license: apache-2.0 |
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base_model: mistralai/Mistral-7B-v0.1 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: zephyr-ds |
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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-ds |
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This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6366 |
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- Rewards/chosen: 0.0331 |
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- Rewards/rejected: -0.0356 |
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- Rewards/accuracies: 0.6320 |
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- Rewards/margins: 0.0687 |
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- Logps/rejected: -250.3080 |
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- Logps/chosen: -272.9035 |
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- Logits/rejected: -2.5200 |
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- Logits/chosen: -2.5064 |
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- Use Label: 9174.8564 |
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- Pred Label: 6857.1440 |
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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: 4 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 16 |
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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 | Use Label | Pred Label | |
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|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:---------:|:----------:| |
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| 0.6393 | 1.0 | 955 | 0.6366 | 0.0331 | -0.0356 | 0.6320 | 0.0687 | -250.3080 | -272.9035 | -2.5200 | -2.5064 | 8966.8564 | 6565.1440 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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