t5_summarize / README.md
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metadata
license: apache-2.0
base_model: google-t5/t5-small
tags:
  - generated_from_trainer
model-index:
  - name: t5_summarize
    results: []

t5_summarize

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

  • Loss: 2.6492
  • Evaluation Runtime: 28.4792
  • Rounded Rouge Scores: {'rouge1': 0.174, 'rouge2': 0.0607, 'rougeL': 0.1367, 'rougeLsum': 0.1369}

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: 4
  • eval_batch_size: 4
  • 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 Evaluation Runtime Rounded Rouge Scores
2.7245 1.0 500 2.6814 29.2864 {'rouge1': 0.1697, 'rouge2': 0.0584, 'rougeL': 0.1344, 'rougeLsum': 0.1345}
2.7318 2.0 1000 2.6707 27.6464 {'rouge1': 0.1735, 'rouge2': 0.0597, 'rougeL': 0.1372, 'rougeLsum': 0.1373}
2.7164 3.0 1500 2.6646 27.3926 {'rouge1': 0.1734, 'rouge2': 0.06, 'rougeL': 0.1371, 'rougeLsum': 0.1372}
2.7054 4.0 2000 2.6600 27.3819 {'rouge1': 0.1739, 'rouge2': 0.0599, 'rougeL': 0.1367, 'rougeLsum': 0.1368}
2.6955 5.0 2500 2.6581 27.9933 {'rouge1': 0.1731, 'rouge2': 0.0601, 'rougeL': 0.1361, 'rougeLsum': 0.1361}
2.6865 6.0 3000 2.6535 28.2157 {'rouge1': 0.1733, 'rouge2': 0.0603, 'rougeL': 0.1363, 'rougeLsum': 0.1364}
2.6821 7.0 3500 2.6521 29.0758 {'rouge1': 0.174, 'rouge2': 0.0606, 'rougeL': 0.1366, 'rougeLsum': 0.1369}
2.681 8.0 4000 2.6508 31.2621 {'rouge1': 0.1743, 'rouge2': 0.0609, 'rougeL': 0.1367, 'rougeLsum': 0.1369}
2.6771 9.0 4500 2.6499 30.4251 {'rouge1': 0.1735, 'rouge2': 0.0605, 'rougeL': 0.1364, 'rougeLsum': 0.1365}
2.6751 10.0 5000 2.6492 28.4792 {'rouge1': 0.174, 'rouge2': 0.0607, 'rougeL': 0.1367, 'rougeLsum': 0.1369}

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2