ubikpt's picture
update model card README.md
7fe47a7
metadata
license: apache-2.0
tags:
  - summarization
  - generated_from_trainer
datasets:
  - cnn_dailymail
metrics:
  - rouge
model-index:
  - name: t5-small-finetuned-cnn
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: cnn_dailymail
          type: cnn_dailymail
          args: 3.0.0
        metrics:
          - name: Rouge1
            type: rouge
            value: 33.2082

t5-small-finetuned-cnn

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

  • Loss: 1.8436
  • Rouge1: 33.2082
  • Rouge2: 16.798
  • Rougel: 28.9573
  • Rougelsum: 31.1044

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: 5.6e-05
  • 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
  • num_epochs: 8

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
2.3793 1.0 359 1.8885 33.0321 16.7798 28.9367 30.9509
2.1432 2.0 718 1.8481 33.1559 16.8557 29.015 31.1122
2.0571 3.0 1077 1.8391 32.99 16.716 28.8118 30.9178
2.0001 4.0 1436 1.8357 33.0543 16.6731 28.8375 30.9604
1.9609 5.0 1795 1.8437 33.1019 16.7576 28.8669 31.001
1.925 6.0 2154 1.8402 33.1388 16.7539 28.8887 31.0262
1.9036 7.0 2513 1.8423 33.1825 16.759 28.9154 31.0656
1.8821 8.0 2872 1.8436 33.2082 16.798 28.9573 31.1044

Framework versions

  • Transformers 4.14.0
  • Pytorch 1.5.0
  • Datasets 2.3.2
  • Tokenizers 0.10.3