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--- |
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license: other |
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library_name: peft |
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tags: |
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- alignment-handbook |
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- trl |
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- dpo |
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- generated_from_trainer |
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base_model: meta-llama/Meta-Llama-3-8B |
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datasets: |
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- EllieS/Temp-L2-DPO |
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model-index: |
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- name: llama3-L1-SFT-L2-DPO |
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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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# llama3-L1-SFT-L2-DPO |
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This model is a fine-tuned version of [EllieS/TempReason-L1-llama3](https://huggingface.co/EllieS/TempReason-L1-llama3) on the EllieS/Temp-L2-DPO dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0028 |
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- Rewards/chosen: -0.4016 |
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- Rewards/rejected: -9.3312 |
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- Rewards/accuracies: 1.0 |
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- Rewards/margins: 8.9296 |
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- Logps/rejected: -994.2072 |
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- Logps/chosen: -84.5141 |
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- Logits/rejected: 1.5698 |
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- Logits/chosen: 0.6541 |
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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-06 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 4 |
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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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| 0.0033 | 0.2497 | 1000 | 0.0065 | -0.3610 | -7.6953 | 1.0 | 7.3344 | -830.6234 | -80.4518 | 1.5489 | 0.7452 | |
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| 0.0013 | 0.4995 | 2000 | 0.0031 | -0.3798 | -9.1892 | 1.0 | 8.8094 | -980.0131 | -82.3365 | 1.5546 | 0.6455 | |
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| 0.0019 | 0.7492 | 3000 | 0.0028 | -0.3966 | -9.3440 | 1.0 | 8.9474 | -995.4902 | -84.0208 | 1.5703 | 0.6568 | |
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| 0.0011 | 0.9989 | 4000 | 0.0028 | -0.4016 | -9.3312 | 1.0 | 8.9296 | -994.2072 | -84.5141 | 1.5698 | 0.6541 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.40.2 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
