Turkish2 / README.md
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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - opus_infopankki
metrics:
  - bleu
model-index:
  - name: opus-mt-tr-en-finetuned-tr-to-en
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: opus_infopankki
          type: opus_infopankki
          args: en-tr
        metrics:
          - name: Bleu
            type: bleu
            value: 56.617

opus-mt-tr-en-finetuned-tr-to-en

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

  • Loss: 0.6321
  • Bleu: 56.617
  • Gen Len: 13.5983

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-06
  • train_batch_size: 64
  • eval_batch_size: 64
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
No log 1.0 241 1.2487 41.0053 13.0461
No log 2.0 482 1.1630 43.1077 13.0386
1.4091 3.0 723 1.0992 44.6583 13.0445
1.4091 4.0 964 1.0463 45.5931 13.0289
1.2325 5.0 1205 1.0012 46.7039 12.9998
1.2325 6.0 1446 0.9610 47.6783 13.0274
1.1284 7.0 1687 0.9262 48.622 12.9866
1.1284 8.0 1928 0.8939 48.4984 13.5762
1.0486 9.0 2169 0.8642 49.1496 13.5918
1.0486 10.0 2410 0.8391 49.8875 13.5905
0.9866 11.0 2651 0.8150 50.6447 13.5803
0.9866 12.0 2892 0.7941 51.2059 13.5731
0.9362 13.0 3133 0.7741 51.7071 13.5754
0.9362 14.0 3374 0.7564 52.4185 13.5781
0.8928 15.0 3615 0.7398 53.0814 13.5744
0.8928 16.0 3856 0.7247 53.5711 13.5783
0.8598 17.0 4097 0.7111 54.0559 13.568
0.8598 18.0 4338 0.6988 54.5188 13.5598
0.8274 19.0 4579 0.6876 54.78 13.5765
0.8274 20.0 4820 0.6780 55.1494 13.5762
0.8086 21.0 5061 0.6688 55.5813 13.5788
0.8086 22.0 5302 0.6610 55.6403 13.5796
0.7878 23.0 5543 0.6539 55.7731 13.5989
0.7878 24.0 5784 0.6483 55.9956 13.593
0.7718 25.0 6025 0.6432 56.2303 13.5904
0.7718 26.0 6266 0.6390 56.4825 13.5975
0.7633 27.0 6507 0.6360 56.5334 13.5958
0.7633 28.0 6748 0.6338 56.5357 13.5965
0.7633 29.0 6989 0.6325 56.5862 13.5974
0.7584 30.0 7230 0.6321 56.617 13.5983

Framework versions

  • Transformers 4.20.1
  • Pytorch 1.12.0
  • Datasets 2.3.2
  • Tokenizers 0.12.1