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--- |
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license: cc-by-4.0 |
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base_model: Helsinki-NLP/opus-mt-tc-big-hu-en |
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tags: |
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- generated_from_trainer |
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metrics: |
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- bleu |
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model-index: |
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- name: opus-mt-tc-big-hu-en-finetuned-news |
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results: [] |
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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-tc-big-hu-en-finetuned-news |
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This model is a fine-tuned version of [Helsinki-NLP/opus-mt-tc-big-hu-en](https://huggingface.co/Helsinki-NLP/opus-mt-tc-big-hu-en) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1412 |
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- Bleu: 40.3642 |
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- Gen Len: 44.0303 |
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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: 5e-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: 3 |
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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 | 0.11 | 100 | 1.1822 | 38.1953 | 43.5551 | |
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| No log | 0.22 | 200 | 1.1738 | 38.6712 | 43.549 | |
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| No log | 0.32 | 300 | 1.1602 | 39.2014 | 44.2009 | |
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| No log | 0.43 | 400 | 1.1503 | 39.2141 | 43.9468 | |
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| 1.2199 | 0.54 | 500 | 1.1451 | 39.2687 | 43.6871 | |
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| 1.2199 | 0.65 | 600 | 1.1349 | 39.445 | 43.9483 | |
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| 1.2199 | 0.75 | 700 | 1.1356 | 39.3787 | 43.47 | |
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| 1.2199 | 0.86 | 800 | 1.1233 | 39.7025 | 43.9054 | |
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| 1.2199 | 0.97 | 900 | 1.1224 | 39.9764 | 43.9656 | |
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| 1.1308 | 1.08 | 1000 | 1.1343 | 39.8533 | 43.9929 | |
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| 1.1308 | 1.19 | 1100 | 1.1446 | 39.7232 | 43.675 | |
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| 1.1308 | 1.29 | 1200 | 1.1378 | 40.0687 | 44.0606 | |
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| 1.1308 | 1.4 | 1300 | 1.1324 | 39.9239 | 43.7738 | |
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| 1.1308 | 1.51 | 1400 | 1.1330 | 40.0318 | 43.7756 | |
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| 0.8661 | 1.62 | 1500 | 1.1315 | 39.8677 | 43.7542 | |
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| 0.8661 | 1.72 | 1600 | 1.1185 | 40.1978 | 44.168 | |
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| 0.8661 | 1.83 | 1700 | 1.1298 | 40.254 | 44.0497 | |
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| 0.8661 | 1.94 | 1800 | 1.1191 | 40.2197 | 44.0295 | |
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| 0.8661 | 2.05 | 1900 | 1.1416 | 40.1255 | 44.0534 | |
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| 0.8198 | 2.16 | 2000 | 1.1479 | 40.3099 | 43.9854 | |
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| 0.8198 | 2.26 | 2100 | 1.1495 | 40.3473 | 44.0204 | |
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| 0.8198 | 2.37 | 2200 | 1.1453 | 40.329 | 44.0764 | |
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| 0.8198 | 2.48 | 2300 | 1.1450 | 40.2623 | 44.0944 | |
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| 0.8198 | 2.59 | 2400 | 1.1471 | 40.416 | 44.1797 | |
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| 0.6783 | 2.69 | 2500 | 1.1433 | 40.4645 | 44.0817 | |
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| 0.6783 | 2.8 | 2600 | 1.1405 | 40.4229 | 44.0554 | |
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| 0.6783 | 2.91 | 2700 | 1.1418 | 40.4142 | 44.0493 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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