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--- |
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license: apache-2.0 |
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base_model: Helsinki-NLP/opus-mt-en-ro |
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tags: |
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- generated_from_trainer |
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datasets: |
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- arrow |
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metrics: |
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- bleu |
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model-index: |
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- name: opus-mt-en-bkm |
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results: |
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- task: |
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name: Sequence-to-sequence Language Modeling |
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type: text2text-generation |
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dataset: |
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name: arrow |
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type: arrow |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Bleu |
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type: bleu |
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value: 14.5684 |
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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-en-bkm |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-ro](https://huggingface.co/Helsinki-NLP/opus-mt-en-ro) on the arrow dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1597 |
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- Bleu: 14.5684 |
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- Gen Len: 58.4294 |
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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-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: 25 |
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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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| 3.3983 | 1.0 | 974 | 1.9251 | 3.7894 | 60.1579 | |
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| 1.9429 | 2.0 | 1948 | 1.6720 | 5.7083 | 58.6443 | |
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| 1.7118 | 3.0 | 2922 | 1.5389 | 7.1977 | 58.8536 | |
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| 1.5647 | 4.0 | 3896 | 1.4484 | 8.4631 | 57.9068 | |
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| 1.4611 | 5.0 | 4870 | 1.3836 | 9.5314 | 59.3106 | |
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| 1.3735 | 6.0 | 5844 | 1.3357 | 10.1879 | 59.5501 | |
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| 1.3078 | 7.0 | 6818 | 1.3014 | 10.9172 | 59.4968 | |
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| 1.245 | 8.0 | 7792 | 1.2737 | 11.445 | 59.585 | |
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| 1.2048 | 9.0 | 8766 | 1.2485 | 11.9346 | 58.3275 | |
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| 1.1648 | 10.0 | 9740 | 1.2298 | 12.3049 | 58.7768 | |
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| 1.1272 | 11.0 | 10714 | 1.2176 | 12.7287 | 58.1549 | |
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| 1.086 | 12.0 | 11688 | 1.2043 | 13.0962 | 59.2217 | |
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| 1.0595 | 13.0 | 12662 | 1.1973 | 13.3375 | 58.6736 | |
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| 1.0343 | 14.0 | 13636 | 1.1844 | 13.3963 | 58.2763 | |
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| 1.0174 | 15.0 | 14610 | 1.1797 | 13.7067 | 58.1738 | |
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| 0.9923 | 16.0 | 15584 | 1.1757 | 13.9467 | 59.3246 | |
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| 0.9703 | 17.0 | 16558 | 1.1704 | 14.1023 | 58.9813 | |
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| 0.9589 | 18.0 | 17532 | 1.1663 | 14.2842 | 58.401 | |
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| 0.9472 | 19.0 | 18506 | 1.1662 | 14.2109 | 58.4796 | |
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| 0.9262 | 20.0 | 19480 | 1.1635 | 14.3872 | 58.1601 | |
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| 0.9147 | 21.0 | 20454 | 1.1606 | 14.4983 | 58.7417 | |
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| 0.9162 | 22.0 | 21428 | 1.1630 | 14.5229 | 58.4345 | |
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| 0.9012 | 23.0 | 22402 | 1.1607 | 14.6204 | 58.0767 | |
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| 0.899 | 24.0 | 23376 | 1.1600 | 14.5681 | 58.4357 | |
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| 0.8934 | 25.0 | 24350 | 1.1597 | 14.5684 | 58.4294 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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