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metadata
license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
datasets:
  - opus_books
metrics:
  - bleu
model-index:
  - name: my_awesome_opus_books_model
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: opus_books
          type: opus_books
          config: en-fr
          split: train
          args: en-fr
        metrics:
          - name: Bleu
            type: bleu
            value: 8.665

my_awesome_opus_books_model

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

  • Loss: 1.1887
  • Bleu: 8.665
  • Gen Len: 17.52

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: 0.0002
  • 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: 20

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
1.6522 1.0 6355 1.4220 6.8084 17.5646
1.5046 2.0 12710 1.3440 7.2961 17.5479
1.424 3.0 19065 1.3085 7.6625 17.5388
1.3927 4.0 25420 1.2794 7.8254 17.5447
1.3279 5.0 31775 1.2606 8.0112 17.5417
1.2972 6.0 38130 1.2440 8.159 17.5222
1.263 7.0 44485 1.2328 8.2809 17.5201
1.2414 8.0 50840 1.2263 8.3546 17.5234
1.2216 9.0 57195 1.2144 8.4076 17.537
1.1954 10.0 63550 1.2076 8.425 17.5313
1.1741 11.0 69905 1.2069 8.4543 17.5247
1.1573 12.0 76260 1.1971 8.5306 17.5245
1.1423 13.0 82615 1.1989 8.6061 17.5168
1.1329 14.0 88970 1.1946 8.6169 17.5322
1.1145 15.0 95325 1.1926 8.6135 17.5258
1.1007 16.0 101680 1.1889 8.6164 17.5314
1.1127 17.0 108035 1.1882 8.686 17.5217
1.0888 18.0 114390 1.1884 8.6621 17.5209
1.0737 19.0 120745 1.1883 8.673 17.5209
1.0733 20.0 127100 1.1887 8.665 17.52

Framework versions

  • Transformers 4.32.1
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3