yakazimir's picture
End of training
193f4bd verified
metadata
library_name: transformers
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
  - alignment-handbook
  - trl
  - simpo
  - generated_from_trainer
  - trl
  - simpo
  - generated_from_trainer
datasets:
  - yakazimir/llama3-ultrafeedback-armorm
model-index:
  - name: llama3instruct_-l5-10-0_3-1e-6-2_best
    results: []

llama3instruct_-l5-10-0_3-1e-6-2_best

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

  • Loss: 1.2685
  • Rewards/chosen: -8.0711
  • Rewards/rejected: -19.7238
  • Rewards/accuracies: 0.8675
  • Rewards/margins: 11.6527
  • Logps/rejected: -1.9724
  • Logps/chosen: -0.8071
  • Logits/rejected: -1.3327
  • Logits/chosen: -1.4140

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: 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: 2.0

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
1.4299 0.8743 400 1.4682 -8.3837 -17.5861 0.8705 9.2024 -1.7586 -0.8384 -1.2770 -1.3300
0.7858 1.7486 800 1.2716 -7.9331 -19.2874 0.8614 11.3543 -1.9287 -0.7933 -1.2977 -1.3755

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.2.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.19.1