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--- |
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base_model: meta-llama/Llama-2-7b-hf |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: llama2-7b-dpo-lora-20231129-52 |
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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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# llama2-7b-dpo-lora-20231129-52 |
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This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6869 |
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- Rewards/chosen: 0.0289 |
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- Rewards/rejected: 0.0137 |
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- Rewards/accuracies: 0.5675 |
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- Rewards/margins: 0.0152 |
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- Logps/rejected: -288.6960 |
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- Logps/chosen: -359.9693 |
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- Logits/rejected: -0.3198 |
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- Logits/chosen: -0.1736 |
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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: 2 |
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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: 8 |
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- gradient_accumulation_steps: 32 |
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- total_train_batch_size: 512 |
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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: 3 |
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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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| 0.6911 | 1.0 | 121 | 0.6918 | 0.0084 | 0.0083 | 0.5238 | 0.0001 | -288.7494 | -360.1742 | -0.3206 | -0.1740 | |
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| 0.6892 | 2.0 | 242 | 0.6888 | 0.0170 | 0.0139 | 0.4841 | 0.0032 | -288.6942 | -360.0880 | -0.3202 | -0.1740 | |
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| 0.6867 | 3.0 | 363 | 0.6869 | 0.0289 | 0.0137 | 0.5675 | 0.0152 | -288.6960 | -359.9693 | -0.3198 | -0.1736 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.1 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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