toolalpaca

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

  • Loss: 0.2505

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: 1e-05
  • train_batch_size: 1
  • eval_batch_size: 1
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 2
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 4
  • total_eval_batch_size: 2
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss
0.2781 0.7407 500 0.2681
0.1417 1.4815 1000 0.2399
0.0362 2.2222 1500 0.2555
0.0244 2.9630 2000 0.2507

Framework versions

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