Llama-3.1-8B-Instruct-contracts-Finetuning

This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 5.5752

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: 2.5e-05
  • train_batch_size: 2
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 5
  • training_steps: 6000
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
6.0322 0.0024 500 5.8889
5.9047 0.0048 1000 5.7508
5.8849 0.0073 1500 5.7206
5.8508 0.0097 2000 5.6745
5.7946 0.0121 2500 5.6536
5.8142 0.0145 3000 5.6447
5.715 0.0170 3500 5.6192
5.7378 0.0194 4000 5.6052
5.702 0.0218 4500 5.5940
5.6464 0.0242 5000 5.5837
5.6911 0.0266 5500 5.5782
5.749 0.0291 6000 5.5752

Framework versions

  • PEFT 0.13.2
  • Transformers 4.46.1
  • Pytorch 2.4.0+cu121
  • Datasets 3.0.1
  • Tokenizers 0.20.1
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