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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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- llama-factory |
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- lora |
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- generated_from_trainer |
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base_model: meta-llama/Meta-Llama-3-8B |
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model-index: |
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- name: sft_trained_woaqa_llama3_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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# sft_trained_woaqa_llama3_dpo |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on the sft_wo_aqa_pref dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.0569 |
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- Rewards/chosen: 9.0148 |
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- Rewards/rejected: 7.8220 |
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- Rewards/accuracies: 0.6667 |
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- Rewards/margins: 1.1928 |
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- Logps/rejected: -180.5298 |
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- Logps/chosen: -151.5047 |
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- Logits/rejected: -1.4439 |
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- Logits/chosen: -1.4397 |
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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-05 |
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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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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 8 |
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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_steps: 0.1 |
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- num_epochs: 3.0 |
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- mixed_precision_training: Native AMP |
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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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| 1.3287 | 0.33 | 200 | 1.8699 | 9.9343 | 9.1282 | 0.6312 | 0.8061 | -167.4677 | -142.3102 | -1.1863 | -1.1862 | |
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| 1.1821 | 0.67 | 400 | 1.9729 | 9.9379 | 9.2024 | 0.6113 | 0.7354 | -166.7256 | -142.2745 | -1.2732 | -1.2718 | |
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| 0.9116 | 1.0 | 600 | 1.9455 | 9.7997 | 8.9466 | 0.6482 | 0.8531 | -169.2835 | -143.6562 | -1.3527 | -1.3510 | |
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| 0.8412 | 1.33 | 800 | 2.0041 | 9.5449 | 8.5167 | 0.6397 | 1.0282 | -173.5831 | -146.2043 | -1.4206 | -1.4179 | |
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| 0.7345 | 1.67 | 1000 | 2.0659 | 9.1494 | 8.1514 | 0.6426 | 0.9980 | -177.2357 | -150.1593 | -1.4325 | -1.4290 | |
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| 0.6609 | 2.0 | 1200 | 2.0321 | 9.0327 | 7.8126 | 0.6681 | 1.2200 | -180.6237 | -151.3265 | -1.4359 | -1.4321 | |
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| 0.6768 | 2.33 | 1400 | 2.0313 | 9.1007 | 7.8929 | 0.6709 | 1.2079 | -179.8211 | -150.6457 | -1.4472 | -1.4432 | |
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| 0.615 | 2.67 | 1600 | 2.0515 | 9.0972 | 7.9582 | 0.6624 | 1.1390 | -179.1680 | -150.6812 | -1.4413 | -1.4370 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
