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metadata
license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: T5-small-summarization
    results: []

T5-small-summarization

This model is a fine-tuned version of t5-small on the truncated version of Samsum dataset. It achieves the following results on the evaluation set:

  • Loss: 1.9294
  • Rouge1: 0.3772
  • Rouge2: 0.1453
  • Rougel: 0.3105
  • Rougelsum: 0.3106
  • Gen Len: 16.1832

Model description

This model performs the summarization of Texts.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 32
  • eval_batch_size: 32
  • 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
No log 1.0 63 2.1165 0.338 0.1186 0.2811 0.2813 16.7595
No log 2.0 126 2.0210 0.3612 0.1338 0.2982 0.2985 16.5592
No log 3.0 189 1.9838 0.3652 0.1384 0.3034 0.304 16.1197
No log 4.0 252 1.9623 0.3715 0.142 0.3077 0.3079 16.2308
No log 5.0 315 1.9513 0.3727 0.1441 0.308 0.3084 16.1453
No log 6.0 378 1.9419 0.375 0.1438 0.309 0.3093 16.2234
No log 7.0 441 1.9376 0.3748 0.144 0.3102 0.3104 16.1465
2.2452 8.0 504 1.9324 0.3754 0.1451 0.3098 0.3099 16.1893
2.2452 9.0 567 1.9302 0.3769 0.1459 0.3112 0.3113 16.1966
2.2452 10.0 630 1.9294 0.3772 0.1453 0.3105 0.3106 16.1832

Framework versions

  • Transformers 4.37.0
  • Pytorch 2.1.2
  • Datasets 2.1.0
  • Tokenizers 0.15.1