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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_j-full-0911 |
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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_j-full-0911 |
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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: 1.4373 |
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- Rewards/chosen: -14.1493 |
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- Rewards/rejected: -15.5710 |
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- Rewards/accuracies: 0.6543 |
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- Rewards/margins: 1.4217 |
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- Logps/rejected: -155.7095 |
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- Logps/chosen: -141.4926 |
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- Logits/rejected: -0.1136 |
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- Logits/chosen: -0.1476 |
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- Nll Loss: 0.1725 |
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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: 5 |
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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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| 1.4367 | 0.9986 | 432 | 1.3926 | -17.0679 | -18.0962 | 0.6565 | 1.0283 | -180.9624 | -170.6792 | -0.4080 | -0.4373 | 0.3200 | |
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| 0.5472 | 1.9994 | 865 | 1.2973 | -16.2909 | -17.5852 | 0.6587 | 1.2944 | -175.8523 | -162.9086 | -0.5434 | -0.5688 | 0.2148 | |
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| 0.2244 | 2.9980 | 1297 | 1.3861 | -15.7105 | -17.2195 | 0.6565 | 1.5089 | -172.1945 | -157.1052 | -0.3428 | -0.3715 | 0.2034 | |
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| 0.1472 | 3.9988 | 1730 | 1.4029 | -14.6462 | -16.1385 | 0.6522 | 1.4923 | -161.3849 | -146.4623 | -0.2701 | -0.3029 | 0.1876 | |
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| 0.1143 | 4.9928 | 2160 | 1.4373 | -14.1493 | -15.5710 | 0.6543 | 1.4217 | -155.7095 | -141.4926 | -0.1136 | -0.1476 | 0.1725 | |
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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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