| library_name: transformers | |
| base_model: facebook/mbart-large-50-many-to-many-mmt | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - iva_mt_wslot | |
| metrics: | |
| - bleu | |
| model-index: | |
| - name: mbart-translation | |
| results: | |
| - task: | |
| name: Sequence-to-sequence Language Modeling | |
| type: text2text-generation | |
| dataset: | |
| name: iva_mt_wslot | |
| type: iva_mt_wslot | |
| config: en-pl | |
| split: validation | |
| args: en-pl | |
| metrics: | |
| - name: Bleu | |
| type: bleu | |
| value: 40.615 | |
| <!-- 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. --> | |
| # mbart-translation | |
| This model is a fine-tuned version of [facebook/mbart-large-50-many-to-many-mmt](https://huggingface.co/facebook/mbart-large-50-many-to-many-mmt) on the iva_mt_wslot dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 1.0132 | |
| - Bleu: 40.615 | |
| - Gen Len: 14.4961 | |
| ## 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: 5e-05 | |
| - train_batch_size: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments | |
| - lr_scheduler_type: linear | |
| - num_epochs: 1 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len | | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:| | |
| | 1.0632 | 1.0 | 2546 | 1.0132 | 40.615 | 14.4961 | | |
| ### Framework versions | |
| - Transformers 4.46.2 | |
| - Pytorch 2.5.1+cu121 | |
| - Datasets 3.1.0 | |
| - Tokenizers 0.20.3 | |