t2_25k_v2_tag4_processed

This model is a fine-tuned version of meta-llama/Llama-3.1-8B-Instruct on the t2_25k_v2_tag4_processed dataset. It achieves the following results on the evaluation set:

  • Loss: 0.2940

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-06
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • total_train_batch_size: 8
  • total_eval_batch_size: 8
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • num_epochs: 1

Training results

Training Loss Epoch Step Validation Loss
0.2961 0.2577 100 0.3410
0.2728 0.5155 200 0.3130
0.2914 0.7732 300 0.2944

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.6.0+cu124
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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