opus-mt-en-bkm / README.md
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metadata
license: apache-2.0
base_model: Helsinki-NLP/opus-mt-en-ro
tags:
  - generated_from_trainer
datasets:
  - arrow
metrics:
  - bleu
model-index:
  - name: opus-mt-en-bkm
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: arrow
          type: arrow
          config: default
          split: train
          args: default
        metrics:
          - name: Bleu
            type: bleu
            value: 14.5684

opus-mt-en-bkm

This model is a fine-tuned version of Helsinki-NLP/opus-mt-en-ro on the arrow dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1597
  • Bleu: 14.5684
  • Gen Len: 58.4294

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: 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: 25

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
3.3983 1.0 974 1.9251 3.7894 60.1579
1.9429 2.0 1948 1.6720 5.7083 58.6443
1.7118 3.0 2922 1.5389 7.1977 58.8536
1.5647 4.0 3896 1.4484 8.4631 57.9068
1.4611 5.0 4870 1.3836 9.5314 59.3106
1.3735 6.0 5844 1.3357 10.1879 59.5501
1.3078 7.0 6818 1.3014 10.9172 59.4968
1.245 8.0 7792 1.2737 11.445 59.585
1.2048 9.0 8766 1.2485 11.9346 58.3275
1.1648 10.0 9740 1.2298 12.3049 58.7768
1.1272 11.0 10714 1.2176 12.7287 58.1549
1.086 12.0 11688 1.2043 13.0962 59.2217
1.0595 13.0 12662 1.1973 13.3375 58.6736
1.0343 14.0 13636 1.1844 13.3963 58.2763
1.0174 15.0 14610 1.1797 13.7067 58.1738
0.9923 16.0 15584 1.1757 13.9467 59.3246
0.9703 17.0 16558 1.1704 14.1023 58.9813
0.9589 18.0 17532 1.1663 14.2842 58.401
0.9472 19.0 18506 1.1662 14.2109 58.4796
0.9262 20.0 19480 1.1635 14.3872 58.1601
0.9147 21.0 20454 1.1606 14.4983 58.7417
0.9162 22.0 21428 1.1630 14.5229 58.4345
0.9012 23.0 22402 1.1607 14.6204 58.0767
0.899 24.0 23376 1.1600 14.5681 58.4357
0.8934 25.0 24350 1.1597 14.5684 58.4294

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.1+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.2