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metadata
license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: t5-small-MedicoSummarizer
    results: []

t5-small-MedicoSummarizer

This model is a fine-tuned version of t5-small on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 2.9737
  • Rouge1: 0.3207
  • Rouge2: 0.0752
  • Rougel: 0.1949
  • Rougelsum: 0.1947
  • Gen Len: 122.586

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: 2e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
3.4289 1.0 625 3.0929 0.3181 0.0722 0.1893 0.1893 122.637
3.2654 2.0 1250 3.0531 0.3199 0.0733 0.1915 0.1916 122.072
3.2288 3.0 1875 3.0245 0.317 0.0725 0.1917 0.1917 122.153
3.178 4.0 2500 3.0097 0.3161 0.0724 0.1907 0.1907 122.398
3.16 5.0 3125 2.9940 0.3162 0.0722 0.192 0.1918 122.114
3.1517 6.0 3750 2.9869 0.3165 0.0728 0.1928 0.1926 122.652
3.1429 7.0 4375 2.9815 0.3189 0.0741 0.1935 0.1933 122.481
3.1226 8.0 5000 2.9761 0.3195 0.0755 0.194 0.1938 122.724
3.1259 9.0 5625 2.9747 0.3208 0.0755 0.1949 0.1947 122.551
3.1151 10.0 6250 2.9737 0.3207 0.0752 0.1949 0.1947 122.586

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0