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Llama2_AAID_structured_train

This model is a fine-tuned version of meta-llama/Llama-2-7b-hf on the AAID_structured dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4973

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: 0.0003
  • train_batch_size: 32
  • eval_batch_size: 32
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 256
  • 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
1.1654 0.0109 10 0.5499
0.4462 0.0219 20 0.5070
0.3949 0.0328 30 0.4973
0.3903 0.0438 40 0.5445
0.3617 0.0547 50 0.5150
0.3346 0.0656 60 0.5359
0.3284 0.0766 70 0.5421
0.3215 0.0875 80 0.5326

Framework versions

  • PEFT 0.11.1
  • Transformers 4.41.1
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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