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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-cpo-beta-0.1
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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-cpo-beta-0.1
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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: 1.3274
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- Rewards/chosen: -13.1885
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- Rewards/rejected: -14.3989
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- Rewards/accuracies: 0.7016
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- Rewards/margins: 1.2104
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- Logps/rejected: -143.9887
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- Logps/chosen: -131.8848
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- Logits/rejected: 0.2135
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- Logits/chosen: 0.1708
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- Nll Loss: 0.3287
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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: 16
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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- total_eval_batch_size: 64
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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 | Nll Loss |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|
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| 1.2968 | 0.8547 | 400 | 1.3274 | -13.1885 | -14.3989 | 0.7016 | 1.2104 | -143.9887 | -131.8848 | 0.2135 | 0.1708 | 0.3287 |
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### Framework versions
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- Transformers 4.41.2
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- Pytorch 2.3.0+rocm6.0
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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This repository contains the model release for the use of [CPO](https://arxiv.org/abs/2401.08417), please find more details in [our github](https://github.com/fe1ixxu/CPO_SIMPO)!
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