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--- |
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license: llama3 |
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base_model: meta-llama/Meta-Llama-3-8B-Instruct |
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tags: |
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- alignment_handbook-handbook |
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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: Meta-Llama-3-8B-Instruct-6e-7 |
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results: [] |
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--- |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-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: 1.2416 |
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- Rewards/chosen: -0.3361 |
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- Rewards/rejected: -0.4013 |
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- Rewards/accuracies: 0.5915 |
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- Rewards/margins: 0.0652 |
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- Logps/rejected: -0.4013 |
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- Logps/chosen: -0.3361 |
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- Logits/rejected: 0.0031 |
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- Logits/chosen: 0.0123 |
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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: 6e-07 |
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- train_batch_size: 2 |
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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: 16 |
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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: cosine |
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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 | |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 1.2443 | 0.8550 | 400 | 1.2416 | -0.3361 | -0.4013 | 0.5915 | 0.0652 | -0.4013 | -0.3361 | 0.0031 | 0.0123 | |
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### Framework versions |
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- Transformers 4.42.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.14.6 |
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- Tokenizers 0.19.1 |
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