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metadata
license: apache-2.0
base_model: GanjinZero/biobart-base
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: fine-tuned-BioBART-15-epochs-1024-input-128-output
    results: []

fine-tuned-BioBART-15-epochs-1024-input-128-output

This model is a fine-tuned version of GanjinZero/biobart-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.5422
  • Rouge1: 0.1912
  • Rouge2: 0.042
  • Rougel: 0.1492
  • Rougelsum: 0.15
  • Gen Len: 29.97

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: 0.0001
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 15

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 151 5.4038 0.0026 0.0006 0.0024 0.0024 5.98
No log 2.0 302 1.8682 0.0475 0.0066 0.0452 0.043 6.59
No log 3.0 453 1.6512 0.0753 0.0169 0.0587 0.0586 22.62
4.1375 4.0 604 1.5702 0.1472 0.0366 0.1124 0.1113 42.92
4.1375 5.0 755 1.5256 0.167 0.0337 0.1309 0.1305 45.89
4.1375 6.0 906 1.5057 0.1435 0.0305 0.1132 0.1134 32.45
1.1893 7.0 1057 1.4854 0.1655 0.0388 0.129 0.1295 34.34
1.1893 8.0 1208 1.4845 0.1635 0.0423 0.1238 0.1252 37.77
1.1893 9.0 1359 1.4980 0.1712 0.0363 0.1382 0.1388 29.68
0.8262 10.0 1510 1.5052 0.1917 0.0431 0.1486 0.1497 32.88
0.8262 11.0 1661 1.5167 0.1731 0.0374 0.1402 0.1403 29.9
0.8262 12.0 1812 1.5267 0.1675 0.035 0.1335 0.1337 29.35
0.8262 13.0 1963 1.5329 0.1839 0.0401 0.1465 0.1465 28.23
0.61 14.0 2114 1.5440 0.1904 0.0452 0.1522 0.1527 29.33
0.61 15.0 2265 1.5422 0.1912 0.042 0.1492 0.15 29.97

Framework versions

  • Transformers 4.36.2
  • Pytorch 1.12.1+cu113
  • Datasets 2.16.1
  • Tokenizers 0.15.0