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LVI_albertina-900m-portuguese-ptpt-encoder
liaad/LVI_albertina-900m-portuguese-ptpt-encoder
LVI_albertina-900m-portuguese-ptpt-encoder is a text classification model from liaad. Use it when you need a label for a piece of text. 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
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- deberta-v2
- Access
- Public
- Created
- Mar 21, 2024
- Updated
- Mar 28, 2024
- SHA
- e50bad57
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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. -->
LVI_albertina-900m-portuguese-ptpt-encoder
This model is a fine-tuned version of PORTULAN/albertina-900m-portuguese-ptpt-encoder on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1651
- Accuracy: 0.9832
- F1: 0.9833
- Precision: 0.9779
- Recall: 0.9889
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: 5e-06
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.1273 | 1.0 | 12866 | 0.1718 | 0.9676 | 0.9668 | 0.9914 | 0.9434 |
| 0.1034 | 2.0 | 25732 | 0.1283 | 0.9814 | 0.9813 | 0.9844 | 0.9782 |
| 0.0292 | 3.0 | 38598 | 0.1219 | 0.9850 | 0.9850 | 0.9828 | 0.9872 |
| 0.0251 | 4.0 | 51464 | 0.1203 | 0.9857 | 0.9856 | 0.9901 | 0.9812 |
| 0.013 | 5.0 | 64330 | 0.1240 | 0.9837 | 0.9836 | 0.9896 | 0.9777 |
| 0.0237 | 6.0 | 77196 | 0.1294 | 0.9848 | 0.9849 | 0.9809 | 0.9889 |
| 0.0153 | 7.0 | 90062 | 0.1651 | 0.9832 | 0.9833 | 0.9779 | 0.9889 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Mar 21, 2024
- Updated
- Mar 28, 2024