| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - wmt16 | |
| metrics: | |
| - bleu | |
| base_model: Helsinki-NLP/opus-mt-tr-en | |
| model-index: | |
| - name: opus-mt-tr-en-finetuned-en-to-tr | |
| results: | |
| - task: | |
| type: text2text-generation | |
| name: Sequence-to-sequence Language Modeling | |
| dataset: | |
| name: wmt16 | |
| type: wmt16 | |
| config: tr-en | |
| split: train | |
| args: tr-en | |
| metrics: | |
| - type: bleu | |
| value: 6.471 | |
| name: Bleu | |
| <!-- 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-tr-en-finetuned-en-to-tr | |
| 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 wmt16 dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.9429 | |
| - Bleu: 6.471 | |
| - Gen Len: 56.1688 | |
| ## 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-05 | |
| - train_batch_size: 16 | |
| - eval_batch_size: 16 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 3 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | | |
| |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:| | |
| | 1.5266 | 1.0 | 12860 | 2.2526 | 4.5834 | 55.6563 | | |
| | 1.2588 | 2.0 | 25720 | 2.0113 | 5.9203 | 56.3506 | | |
| | 1.1878 | 3.0 | 38580 | 1.9429 | 6.471 | 56.1688 | | |
| ### Framework versions | |
| - Transformers 4.25.1 | |
| - Pytorch 1.13.1+cu116 | |
| - Datasets 2.8.0 | |
| - Tokenizers 0.13.2 | |