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metadata
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
  - alignment-handbook
  - generated_from_trainer
datasets:
  - simonycl/llama3.1-ultrafeedback-annotate-armorm
model-index:
  - name: llama-3.1-8b-instruct-armorm
    results: []

llama-3.1-8b-instruct-armorm

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the simonycl/llama3.1-ultrafeedback-annotate-armorm dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5123
  • Rewards/chosen: -2.5095
  • Rewards/rejected: -3.2703
  • Rewards/accuracies: 0.7782
  • Rewards/margins: 0.7608
  • Logps/rejected: -600.9280
  • Logps/chosen: -513.8394
  • Logits/rejected: -2.6733
  • Logits/chosen: -2.7845

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: 5e-07
  • train_batch_size: 2
  • eval_batch_size: 4
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 16
  • total_train_batch_size: 128
  • total_eval_batch_size: 16
  • 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
0.2606 0.7886 400 0.5123 -2.5095 -3.2703 0.7782 0.7608 -600.9280 -513.8394 -2.6733 -2.7845

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0+cu121
  • Datasets 2.21.0
  • Tokenizers 0.19.1