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uner_swe_tal
universalner/uner_swe_tal
uner_swe_tal is a token classification model from universalner. 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
- Jun 19, 2024
- Updated
- Jun 19, 2024
- SHA
- 537853b0
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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. -->
uner_swe_tal
This model is a fine-tuned version of xlm-roberta-large on the uner_swe_tal dataset. It achieves the following results on the evaluation set:
- Loss: 0.0144
- Precision: 0.7407
- Recall: 0.8696
- F1: 0.8000
- Accuracy: 0.9985
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
Framework versions
- Transformers 4.31.0
- Pytorch 1.10.1+cu113
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Token Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jun 19, 2024
- Updated
- Jun 19, 2024