| --- |
| library_name: transformers |
| license: mit |
| base_model: xlm-roberta-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - f1 |
| model-index: |
| - name: multilingual-ner-model-with-code23 |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # multilingual-ner-model-with-code23 |
|
|
| This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1351 |
| - F1: 0.8648 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## 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: 24 |
| - eval_batch_size: 24 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:------:| |
| | 0.2603 | 1.0 | 525 | 0.1511 | 0.8240 | |
| | 0.1287 | 2.0 | 1050 | 0.1367 | 0.8492 | |
| | 0.0804 | 3.0 | 1575 | 0.1351 | 0.8648 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.3 |
| - Pytorch 2.9.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.1 |
| |
