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xlm-roberta-base-ka-ner
alexamiredjibi/xlm-roberta-base-ka-ner
xlm-roberta-base-ka-ner is a token classification model from alexamiredjibi. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Nov 16, 2023
- Updated
- Nov 16, 2023
- SHA
- 9a413e3a
Base models
Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
xlm-roberta-base-ka-ner
This model is a fine-tuned version of xlm-roberta-base on the wikiann dataset. It achieves the following results on the evaluation set:
- Loss: 0.2031
- Precision: 0.8506
- Recall: 0.8703
- F1: 0.8603
- Accuracy: 0.9425
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.5349 | 1.0 | 625 | 0.2377 | 0.8302 | 0.8218 | 0.8260 | 0.9287 |
| 0.2353 | 2.0 | 1250 | 0.2037 | 0.8556 | 0.8536 | 0.8546 | 0.9394 |
| 0.1782 | 3.0 | 1875 | 0.2031 | 0.8506 | 0.8703 | 0.8603 | 0.9425 |
Metrics per category
{'LOC': {'precision': 0.8558191459670667, 'recall': 0.9074874223142941, 'f1': 0.8808962941683425, 'number': 16895}, 'ORG': {'precision': 0.7917612346799818, 'recall': 0.7510226049515608, 'f1': 0.7708540492763231, 'number': 9290}, 'PER': {'precision': 0.8896882494004796, 'recall': 0.9157884743188076, 'f1': 0.9025497076023392, 'number': 10533}, 'overall_precision': 0.8505682876839947, 'overall_recall': 0.8702816057519472, 'overall_f1': 0.8603120330609663, 'overall_accuracy': 0.9424682155180856}
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Token Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Languages
- ka
- Created
- Nov 16, 2023
- Updated
- Nov 16, 2023