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--- |
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base_model: meta-llama/Llama-3.1-8B-Instruct |
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library_name: peft |
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license: llama3.1 |
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tags: |
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- llama-factory |
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- lora |
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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: Llama-3.1-8B-Instruct-SAA-600 |
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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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# Llama-3.1-8B-Instruct-SAA-600 |
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This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the bct_non_cot_dpo_600 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0943 |
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- Rewards/chosen: -0.0072 |
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- Rewards/rejected: -0.0623 |
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- Rewards/accuracies: 0.8833 |
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- Rewards/margins: 0.0551 |
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- Logps/rejected: -0.6233 |
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- Logps/chosen: -0.0722 |
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- Logits/rejected: -0.4048 |
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- Logits/chosen: -0.3432 |
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- Sft Loss: 0.0119 |
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- Odds Ratio Loss: 0.8243 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_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: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10.0 |
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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 | Sft Loss | Odds Ratio Loss | |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:---------------:| |
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| 1.3352 | 1.4815 | 50 | 1.0317 | -0.0989 | -0.1576 | 0.8333 | 0.0587 | -1.5758 | -0.9889 | -0.4812 | -0.4002 | 0.1167 | 9.1492 | |
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| 0.2371 | 2.9630 | 100 | 0.1655 | -0.0135 | -0.0699 | 0.8833 | 0.0564 | -0.6987 | -0.1348 | -0.4551 | -0.3813 | 0.0177 | 1.4782 | |
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| 0.1421 | 4.4444 | 150 | 0.1010 | -0.0077 | -0.0577 | 0.8833 | 0.0500 | -0.5773 | -0.0770 | -0.4107 | -0.3473 | 0.0124 | 0.8869 | |
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| 0.1291 | 5.9259 | 200 | 0.0984 | -0.0075 | -0.0594 | 0.8833 | 0.0518 | -0.5936 | -0.0752 | -0.4066 | -0.3442 | 0.0123 | 0.8613 | |
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| 0.1246 | 7.4074 | 250 | 0.0943 | -0.0072 | -0.0623 | 0.8833 | 0.0551 | -0.6233 | -0.0722 | -0.4048 | -0.3432 | 0.0119 | 0.8243 | |
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| 0.1045 | 8.8889 | 300 | 0.0948 | -0.0072 | -0.0628 | 0.8833 | 0.0555 | -0.6277 | -0.0724 | -0.4046 | -0.3432 | 0.0119 | 0.8292 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.45.2 |
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- Pytorch 2.3.0 |
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- Datasets 2.19.0 |
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- Tokenizers 0.20.0 |
