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metadata
tags:
  - generated_from_trainer
datasets:
  - ccmatrix
metrics:
  - bleu
model-index:
  - name: opus-mt-id-en-ccmatrix-no-warmup
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: ccmatrix
          type: ccmatrix
          config: en-id
          split: train
          args: en-id
        metrics:
          - name: Bleu
            type: bleu
            value: 56.6595

opus-mt-id-en-ccmatrix-no-warmup

This model was trained from scratch on the ccmatrix dataset. It achieves the following results on the evaluation set:

  • Loss: 0.9795
  • Bleu: 56.6595

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: 0.0001
  • 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: 25

Training results

Training Loss Epoch Step Validation Loss Bleu
0.8307 1.0 28125 0.8213 50.8248
0.7031 2.0 56250 0.7851 52.0712
0.6426 3.0 84375 0.7716 52.6974
0.5976 4.0 112500 0.7645 53.0742
0.5599 5.0 140625 0.7580 53.6526
0.5265 6.0 168750 0.7610 53.9336
0.4962 7.0 196875 0.7592 54.3884
0.4677 8.0 225000 0.7611 54.4904
0.4404 9.0 253125 0.7680 54.6679
0.4148 10.0 281250 0.7760 54.8934
0.3901 11.0 309375 0.7853 55.1644
0.3662 12.0 337500 0.7945 55.3496
0.3432 13.0 365625 0.8071 55.4056
0.3211 14.0 393750 0.8149 55.5914
0.2995 15.0 421875 0.8314 55.8594
0.2789 16.0 450000 0.8504 55.5482
0.2591 17.0 478125 0.8637 55.8965
0.24 18.0 506250 0.8789 55.9817
0.222 19.0 534375 0.8956 56.046
0.2047 20.0 562500 0.9096 56.1539
0.1888 21.0 590625 0.9279 56.2939
0.1739 22.0 618750 0.9409 56.4546
0.1606 23.0 646875 0.9580 56.5525
0.1488 24.0 675000 0.9713 56.6069
0.1392 25.0 703125 0.9795 56.6595

Framework versions

  • Transformers 4.26.1
  • Pytorch 2.0.0
  • Datasets 2.10.1
  • Tokenizers 0.11.0