context

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

  • Loss: 3.7005
  • Accuracy: 0.4548

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-05
  • train_batch_size: 40
  • eval_batch_size: 40
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 160
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss Accuracy
0.7716 0.6479 500 3.7005 0.4548
0.3675 1.2958 1000 3.8487 0.4565
0.2102 1.9436 1500 3.9705 0.4568
0.1164 2.5915 2000 4.1546 0.4570

Framework versions

  • Transformers 4.45.0.dev0
  • Pytorch 2.3.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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