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bart-base-lora-summarization-medical

This model is a fine-tuned version of facebook/bart-base on the 'mystic-leung/medical_cord19' dataset. It achieves the following results on the evaluation set:

  • Loss: 2.4119
  • Rouge1: 0.4304
  • Rouge2: 0.2352
  • Rougel: 0.3663
  • Rougelsum: 0.3660
  • Gen Len: 18.1767

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: 3e-05
  • train_batch_size: 4
  • eval_batch_size: 1
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
2.5079 1.0 6250 2.121959 0.4263 0.2290 0.3597 0.3594 18.3300
2.4566 2.0 12500 2.084411 0.4267 0.2312 0.3622 0.3618 18.2773
2.4242 3.0 18750 2.061557 0.4311 0.2358 0.3660 0.3656 18.1307
2.4058 4.0 25000 2.053182 0.4316 0.2367 0.3660 0.3659 18.1753
2.4119 5.0 31250 2.052128 0.4304 0.2352 0.3663 0.3660 18.1767

Framework versions

  • PEFT 0.10.0
  • Transformers 4.40.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1
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Dataset used to train zbigi/bart-base-lora-summarization-medical