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--- |
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library_name: transformers |
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license: llama3.1 |
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
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tags: |
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- alignment-handbook |
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- trl |
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- cpo |
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- generated_from_trainer |
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- trl |
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- cpo |
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- generated_from_trainer |
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datasets: |
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- princeton-nlp/llama3-ultrafeedback |
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model-index: |
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- name: llama3.1-cpo-full-0913 |
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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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# llama3.1-cpo-full-0913 |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the princeton-nlp/llama3-ultrafeedback dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.5934 |
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- Rewards/chosen: -15.4936 |
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- Rewards/rejected: -16.2190 |
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- Rewards/accuracies: 0.6261 |
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- Rewards/margins: 0.7255 |
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- Logps/rejected: -162.1901 |
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- Logps/chosen: -154.9355 |
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- Logits/rejected: -0.4926 |
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- Logits/chosen: -0.5160 |
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- Nll Loss: 0.4228 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 4 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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- total_eval_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: linear |
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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 | Nll Loss | |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:| |
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| 1.9304 | 0.2311 | 100 | 1.7873 | -14.9945 | -15.3576 | 0.5804 | 0.3632 | -153.5762 | -149.9445 | -0.3649 | -0.3854 | 0.4085 | |
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| 1.6908 | 0.4623 | 200 | 1.6702 | -15.6437 | -16.2439 | 0.5978 | 0.6002 | -162.4385 | -156.4369 | -0.3777 | -0.4014 | 0.4252 | |
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| 1.6317 | 0.6934 | 300 | 1.6162 | -15.4682 | -16.1519 | 0.6152 | 0.6837 | -161.5185 | -154.6818 | -0.4753 | -0.4948 | 0.4202 | |
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| 1.62 | 0.9246 | 400 | 1.5947 | -15.5964 | -16.3155 | 0.6261 | 0.7192 | -163.1553 | -155.9637 | -0.4910 | -0.5144 | 0.4262 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.3.1 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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