GREEN-RadLlama2-7b / README.md
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metadata
license: llama2
base_model: StanfordAIMI/RadLLaMA-7b
tags:
  - generated_from_trainer
model-index:
  - name: GREEN
    results: []

StanfordAIMI/GREEN

This model is a fine-tuned version of StanfordAIMI/RadLLaMA-7b. It achieves the following results on the evaluation set:

  • Loss: 0.0644

Model description and Training procedure

Please see the project website at https://stanford-aimi.github.io/green.html.

Intended uses & limitations

This model is finetuned to evaluate the difference between the reference and candidate radiology report for Chest Xrays.

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 32
  • total_train_batch_size: 2048
  • total_eval_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.05
  • num_epochs: 3.0

Training results

Training Loss Epoch Step Validation Loss
0.2634 0.64 25 0.2924
0.1216 1.28 50 0.0898
0.0833 1.92 75 0.0718
0.062 2.56 100 0.0644

Framework versions

  • Transformers 4.38.0.dev0
  • Pytorch 2.2.0+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1