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llama-3-8b-instruct-single-judge

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

  • Loss: 0.6593
  • Rewards/chosen: -1.3185
  • Rewards/rejected: -1.5107
  • Rewards/accuracies: 0.5935
  • Rewards/margins: 0.1922
  • Logps/rejected: -301.4192
  • Logps/chosen: -283.3882
  • Logits/rejected: -1.3226
  • Logits/chosen: -1.3593

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: 1
  • eval_batch_size: 2
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 4
  • gradient_accumulation_steps: 32
  • total_train_batch_size: 128
  • total_eval_batch_size: 8
  • 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
0.5714 0.8528 400 0.6593 -1.3185 -1.5107 0.5935 0.1922 -301.4192 -283.3882 -1.3226 -1.3593

Framework versions

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