llm3br256-v

This model is a fine-tuned version of meta-llama/Llama-3.2-3B-Instruct on the Goavanto dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0185

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: 0.0001
  • train_batch_size: 48
  • eval_batch_size: 48
  • seed: 42
  • optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss
0.1227 0.2475 25 0.1074
0.0553 0.4950 50 0.0551
0.0338 0.7426 75 0.0350
0.0302 0.9901 100 0.0277
0.0373 1.2376 125 0.0256
0.0321 1.4851 150 0.0251
0.026 1.7327 175 0.0228
0.029 1.9802 200 0.0212
0.0152 2.2277 225 0.0216
0.011 2.4752 250 0.0205
0.0154 2.7228 275 0.0194
0.021 2.9703 300 0.0192
0.0282 3.2178 325 0.0186
0.007 3.4653 350 0.0181
0.017 3.7129 375 0.0188
0.0315 3.9604 400 0.0185
0.0156 4.2079 425 0.0193
0.0059 4.4554 450 0.0197
0.0136 4.7030 475 0.0198
0.0092 4.9505 500 0.0217
0.008 5.1980 525 0.0189

Framework versions

  • PEFT 0.12.0
  • Transformers 4.46.1
  • Pytorch 2.4.0+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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