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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- opus_infopankki |
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metrics: |
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- bleu |
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base_model: Helsinki-NLP/opus-mt-tr-en |
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model-index: |
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- name: opus-mt-tr-en-finetuned-tr-to-en |
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results: |
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- task: |
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type: text2text-generation |
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name: Sequence-to-sequence Language Modeling |
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dataset: |
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name: opus_infopankki |
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type: opus_infopankki |
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args: en-tr |
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metrics: |
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- type: bleu |
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value: 56.617 |
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name: Bleu |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# opus-mt-tr-en-finetuned-tr-to-en |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-tr-en](https://huggingface.co/Helsinki-NLP/opus-mt-tr-en) on the opus_infopankki dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6321 |
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- Bleu: 56.617 |
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- Gen Len: 13.5983 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-06 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 30 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:| |
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| No log | 1.0 | 241 | 1.2487 | 41.0053 | 13.0461 | |
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| No log | 2.0 | 482 | 1.1630 | 43.1077 | 13.0386 | |
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| 1.4091 | 3.0 | 723 | 1.0992 | 44.6583 | 13.0445 | |
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| 1.4091 | 4.0 | 964 | 1.0463 | 45.5931 | 13.0289 | |
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| 1.2325 | 5.0 | 1205 | 1.0012 | 46.7039 | 12.9998 | |
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| 1.2325 | 6.0 | 1446 | 0.9610 | 47.6783 | 13.0274 | |
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| 1.1284 | 7.0 | 1687 | 0.9262 | 48.622 | 12.9866 | |
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| 1.1284 | 8.0 | 1928 | 0.8939 | 48.4984 | 13.5762 | |
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| 1.0486 | 9.0 | 2169 | 0.8642 | 49.1496 | 13.5918 | |
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| 1.0486 | 10.0 | 2410 | 0.8391 | 49.8875 | 13.5905 | |
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| 0.9866 | 11.0 | 2651 | 0.8150 | 50.6447 | 13.5803 | |
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| 0.9866 | 12.0 | 2892 | 0.7941 | 51.2059 | 13.5731 | |
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| 0.9362 | 13.0 | 3133 | 0.7741 | 51.7071 | 13.5754 | |
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| 0.9362 | 14.0 | 3374 | 0.7564 | 52.4185 | 13.5781 | |
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| 0.8928 | 15.0 | 3615 | 0.7398 | 53.0814 | 13.5744 | |
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| 0.8928 | 16.0 | 3856 | 0.7247 | 53.5711 | 13.5783 | |
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| 0.8598 | 17.0 | 4097 | 0.7111 | 54.0559 | 13.568 | |
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| 0.8598 | 18.0 | 4338 | 0.6988 | 54.5188 | 13.5598 | |
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| 0.8274 | 19.0 | 4579 | 0.6876 | 54.78 | 13.5765 | |
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| 0.8274 | 20.0 | 4820 | 0.6780 | 55.1494 | 13.5762 | |
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| 0.8086 | 21.0 | 5061 | 0.6688 | 55.5813 | 13.5788 | |
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| 0.8086 | 22.0 | 5302 | 0.6610 | 55.6403 | 13.5796 | |
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| 0.7878 | 23.0 | 5543 | 0.6539 | 55.7731 | 13.5989 | |
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| 0.7878 | 24.0 | 5784 | 0.6483 | 55.9956 | 13.593 | |
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| 0.7718 | 25.0 | 6025 | 0.6432 | 56.2303 | 13.5904 | |
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| 0.7718 | 26.0 | 6266 | 0.6390 | 56.4825 | 13.5975 | |
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| 0.7633 | 27.0 | 6507 | 0.6360 | 56.5334 | 13.5958 | |
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| 0.7633 | 28.0 | 6748 | 0.6338 | 56.5357 | 13.5965 | |
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| 0.7633 | 29.0 | 6989 | 0.6325 | 56.5862 | 13.5974 | |
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| 0.7584 | 30.0 | 7230 | 0.6321 | 56.617 | 13.5983 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.12.0 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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