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metadata
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
  - alignment-handbook
  - generated_from_trainer
datasets:
  - princeton-nlp/llama3-ultrafeedback
model-index:
  - name: llama-3-8b-instruct-cpo-beta-0.1
    results: []

llama-3-8b-instruct-cpo-beta-0.1

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the princeton-nlp/llama3-ultrafeedback dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3274
  • Rewards/chosen: -13.1885
  • Rewards/rejected: -14.3989
  • Rewards/accuracies: 0.7016
  • Rewards/margins: 1.2104
  • Logps/rejected: -143.9887
  • Logps/chosen: -131.8848
  • Logits/rejected: 0.2135
  • Logits/chosen: 0.1708
  • Nll Loss: 0.3287

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-06
  • train_batch_size: 2
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 16
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen Nll Loss
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

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+rocm6.0
  • Datasets 2.19.2
  • Tokenizers 0.19.1