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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: XLM_temporal_expression_normalization |
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results: [] |
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language: |
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- es |
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- en |
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- it |
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- fr |
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- eu |
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--- |
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# XLM_normalization_BEST_MODEL |
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This model was trained over the XLM-Large model for temporal expression normalization as a result of the paper "A Novel Methodology for Enhancing |
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Cross-Language and Domain Adaptability in Temporal Expression Normalization" |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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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" |
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## Training and evaluation data |
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All the information about training, evaluation and benchmarking can be found in the paper "A Novel Methodology for Enhancing |
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Cross-Language and Domain Adaptability in Temporal Expression Normalization" |
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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: 8e-05 |
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- train_batch_size: 20 |
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- eval_batch_size: 20 |
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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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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.15.0 |
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- Tokenizers 0.15.0 |
