| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | datasets: |
| | - opus_infopankki |
| | metrics: |
| | - bleu |
| | model-index: |
| | - name: opus-mt-ar-en-finetuned-ar-to-en |
| | results: |
| | - task: |
| | name: Sequence-to-sequence Language Modeling |
| | type: text2text-generation |
| | dataset: |
| | name: opus_infopankki |
| | type: opus_infopankki |
| | args: ar-en |
| | metrics: |
| | - name: Bleu |
| | type: bleu |
| | value: 53.5086 |
| | --- |
| | |
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| | should probably proofread and complete it, then remove this comment. --> |
| |
|
| | # opus-mt-ar-en-finetuned-ar-to-en |
| |
|
| | This model is a fine-tuned version of [Helsinki-NLP/opus-mt-ar-en](https://huggingface.co/Helsinki-NLP/opus-mt-ar-en) on the opus_infopankki dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7636 |
| | - Bleu: 53.5086 |
| | - Gen Len: 13.5728 |
| | |
| | ## 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 | 278 | 1.5114 | 35.2767 | 14.2084 | |
| | | 1.6677 | 2.0 | 556 | 1.4025 | 37.5243 | 14.0245 | |
| | | 1.6677 | 3.0 | 834 | 1.3223 | 39.4262 | 13.8101 | |
| | | 1.4743 | 4.0 | 1112 | 1.2567 | 40.7045 | 13.8533 | |
| | | 1.4743 | 5.0 | 1390 | 1.2001 | 41.8356 | 13.8083 | |
| | | 1.3428 | 6.0 | 1668 | 1.1504 | 43.2448 | 13.6958 | |
| | | 1.3428 | 7.0 | 1946 | 1.1072 | 44.177 | 13.6783 | |
| | | 1.2595 | 8.0 | 2224 | 1.0701 | 45.17 | 13.6587 | |
| | | 1.1829 | 9.0 | 2502 | 1.0345 | 45.9612 | 13.6706 | |
| | | 1.1829 | 10.0 | 2780 | 1.0042 | 46.9009 | 13.6236 | |
| | | 1.1188 | 11.0 | 3058 | 0.9760 | 47.7478 | 13.6205 | |
| | | 1.1188 | 12.0 | 3336 | 0.9505 | 48.3082 | 13.6283 | |
| | | 1.0735 | 13.0 | 3614 | 0.9270 | 48.9782 | 13.6203 | |
| | | 1.0735 | 14.0 | 3892 | 0.9060 | 49.5541 | 13.6311 | |
| | | 1.0269 | 15.0 | 4170 | 0.8869 | 49.9905 | 13.6222 | |
| | | 1.0269 | 16.0 | 4448 | 0.8700 | 50.4806 | 13.6047 | |
| | | 0.9983 | 17.0 | 4726 | 0.8538 | 50.9186 | 13.6159 | |
| | | 0.9647 | 18.0 | 5004 | 0.8398 | 51.3492 | 13.6146 | |
| | | 0.9647 | 19.0 | 5282 | 0.8271 | 51.7219 | 13.5275 | |
| | | 0.9398 | 20.0 | 5560 | 0.8156 | 52.0177 | 13.5756 | |
| | | 0.9398 | 21.0 | 5838 | 0.8053 | 52.3619 | 13.5807 | |
| | | 0.9206 | 22.0 | 6116 | 0.7963 | 52.6051 | 13.5652 | |
| | | 0.9206 | 23.0 | 6394 | 0.7885 | 52.8322 | 13.5669 | |
| | | 0.9012 | 24.0 | 6672 | 0.7818 | 52.9402 | 13.5701 | |
| | | 0.9012 | 25.0 | 6950 | 0.7762 | 53.1182 | 13.5695 | |
| | | 0.8965 | 26.0 | 7228 | 0.7717 | 53.1596 | 13.5612 | |
| | | 0.8836 | 27.0 | 7506 | 0.7681 | 53.3116 | 13.5719 | |
| | | 0.8836 | 28.0 | 7784 | 0.7656 | 53.4399 | 13.5758 | |
| | | 0.8777 | 29.0 | 8062 | 0.7642 | 53.4805 | 13.5737 | |
| | | 0.8777 | 30.0 | 8340 | 0.7636 | 53.5086 | 13.5728 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.20.1 |
| | - Pytorch 1.12.0 |
| | - Datasets 2.3.2 |
| | - Tokenizers 0.12.1 |
| | |
