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--- |
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library_name: peft |
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license: llama3.1 |
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base_model: meta-llama/Llama-3.1-8B-Instruct |
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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_dpo_sg_values_p025_OA_gold |
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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_dpo_sg_values_p025_OA_gold |
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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 dpo_sg_values_p025_OA_gold dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1369 |
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- Rewards/chosen: -0.3243 |
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- Rewards/rejected: -3.7445 |
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- Rewards/accuracies: 0.9400 |
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- Rewards/margins: 3.4202 |
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- Logps/chosen: -5.3343 |
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- Logps/rejected: -44.0676 |
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- Logits/chosen: -0.8235 |
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- Logits/rejected: -0.8529 |
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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: 1e-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: 4 |
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- total_train_batch_size: 8 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 1.0 |
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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/chosen | Logps/rejected | Logits/chosen | Logits/rejected | |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------:|:--------------:|:-------------:|:---------------:| |
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| 0.677 | 0.1495 | 250 | 0.6611 | -0.0030 | -0.0688 | 0.8780 | 0.0658 | -2.1210 | -7.3104 | -0.6673 | -0.6792 | |
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| 0.4141 | 0.2990 | 500 | 0.3328 | -0.1370 | -1.2934 | 0.8960 | 1.1564 | -3.4617 | -19.5564 | -0.7405 | -0.7604 | |
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| 0.1869 | 0.4486 | 750 | 0.1943 | -0.3266 | -2.7983 | 0.9280 | 2.4718 | -5.3572 | -34.6058 | -0.8272 | -0.8525 | |
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| 0.1234 | 0.5981 | 1000 | 0.1579 | -0.3430 | -3.2984 | 0.9380 | 2.9554 | -5.5213 | -39.6065 | -0.8336 | -0.8610 | |
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| 0.122 | 0.7476 | 1250 | 0.1439 | -0.3187 | -3.5609 | 0.9360 | 3.2422 | -5.2784 | -42.2310 | -0.8265 | -0.8553 | |
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| 0.0821 | 0.8971 | 1500 | 0.1398 | -0.3263 | -3.7101 | 0.9340 | 3.3838 | -5.3544 | -43.7234 | -0.8241 | -0.8535 | |
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### Framework versions |
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- PEFT 0.15.2 |
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- Transformers 4.49.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 2.21.0 |
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- Tokenizers 0.21.1 |
