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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 |
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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: llama-3-8b-instruct-simpo |
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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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# llama-3-8b-instruct-simpo |
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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: 1.3755 |
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- Rewards/chosen: -2.9448 |
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- Rewards/rejected: -3.6038 |
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- Rewards/accuracies: 0.6613 |
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- Rewards/margins: 0.6589 |
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- Logps/rejected: -1.4415 |
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- Logps/chosen: -1.1779 |
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- Logits/rejected: -1.1545 |
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- Logits/chosen: -1.1873 |
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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: 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: 8 |
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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: 32 |
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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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| 1.3975 | 0.8549 | 400 | 1.3755 | -2.9448 | -3.6038 | 0.6613 | 0.6589 | -1.4415 | -1.1779 | -1.1545 | -1.1873 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.2.2+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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