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README.md
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---
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base_model: meta-llama/Meta-Llama-3.1-8B
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library_name: peft
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license: llama3.1
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tags:
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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: dpo-llama3-8b-sample-rules
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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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# dpo-llama3-8b-sample-rules
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1841
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- Rewards/chosen: 0.0866
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- Rewards/rejected: -1.6352
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- Rewards/accuracies: 1.0
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- Rewards/margins: 1.7218
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- Logps/rejected: -545.1958
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- Logps/chosen: -202.5652
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- Logits/rejected: -1.3753
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- Logits/chosen: -1.2073
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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: 2
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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_ratio: 0.1
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- num_epochs: 1
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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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| 0.4281 | 0.4444 | 50 | 0.3902 | 0.1843 | -0.5815 | 1.0 | 0.7658 | -439.8294 | -192.8043 | -1.3883 | -1.2422 |
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| 0.193 | 0.8889 | 100 | 0.1841 | 0.0866 | -1.6352 | 1.0 | 1.7218 | -545.1958 | -202.5652 | -1.3753 | -1.2073 |
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### Framework versions
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- PEFT 0.12.0
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- Transformers 4.44.0
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- Pytorch 2.3.1+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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