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beto-pos
hugo-albert/beto-pos
beto-pos is a token classification model from hugo-albert. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Oct 11, 2024
- Updated
- Oct 28, 2024
- SHA
- eb127c82
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Base models
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. -->
beto-pos
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0894
- Precision: 0.9797
- Recall: 0.9815
- F1: 0.9806
- Accuracy: 0.9811
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: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|---|
| 0.4515 | 1.0 | 603 | 0.1079 | 0.9737 | 0.9760 | 0.9749 | 0.9763 |
| 0.0607 | 2.0 | 1206 | 0.0957 | 0.9785 | 0.9803 | 0.9794 | 0.9798 |
| 0.0344 | 3.0 | 1809 | 0.0894 | 0.9797 | 0.9815 | 0.9806 | 0.9811 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.0.2
- Tokenizers 0.19.1
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- Created
- Oct 11, 2024
- Updated
- Oct 28, 2024