| --- |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: XLM_temporal_expression_normalization |
| results: [] |
| language: |
| - es |
| - en |
| - it |
| - fr |
| - eu |
| --- |
| |
| # XLM_normalization_BEST_MODEL |
| |
| This model was trained over the XLM-Large model for temporal expression normalization as a result of the paper "A Novel Methodology for Enhancing |
| Cross-Language and Domain Adaptability in Temporal Expression Normalization" |
| |
| ## Model description |
| |
| More information needed |
| |
| ## Intended uses & limitations |
| |
| This model requires from extra post-processing. The proper code can be found at "https://github.com/asdc-s5/Temporal-expression-normalization-with-fill-mask" |
| |
| ## Training and evaluation data |
| |
| All the information about training, evaluation and benchmarking can be found in the paper "A Novel Methodology for Enhancing |
| Cross-Language and Domain Adaptability in Temporal Expression Normalization" |
| |
| ## Training procedure |
| |
| ### Training hyperparameters |
| |
| The following hyperparameters were used during training: |
| - learning_rate: 8e-05 |
| - train_batch_size: 20 |
| - eval_batch_size: 20 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
| |
| ### Framework versions |
| |
| - Transformers 4.35.2 |
| - Pytorch 2.1.1+cu121 |
| - Datasets 2.15.0 |
| - Tokenizers 0.15.0 |
