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profesion-tw-class
MorcuendeA/profesion-tw-class
profesion-tw-class is a text classification model from MorcuendeA. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- roberta
- Access
- Public
- Created
- Jul 12, 2025
- Updated
- Jul 12, 2025
- SHA
- 46d5be59
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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. -->
modelo_test
This model is a fine-tuned version of PlanTL-GOB-ES/roberta-large-bne on the luisgasco/profner_classification_master dataset. It achieves the following results on the evaluation set:
- Loss: 0.2443
- Accuracy: 0.9619
- F1 Score: 0.9224
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 69
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 6
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Score |
|---|---|---|---|---|---|
| 0.5843 | 0.2865 | 50 | 0.3705 | 0.83 | 0.7231 |
| 0.2483 | 0.5731 | 100 | 0.1913 | 0.942 | 0.8872 |
| 0.2024 | 0.8596 | 150 | 0.1619 | 0.954 | 0.9091 |
| 0.1972 | 1.1433 | 200 | 0.2304 | 0.942 | 0.8872 |
| 0.1093 | 1.4298 | 250 | 0.2269 | 0.958 | 0.9157 |
| 0.0658 | 1.7163 | 300 | 0.2079 | 0.956 | 0.9098 |
| 0.0806 | 2.0 | 350 | 0.2081 | 0.954 | 0.9076 |
| 0.0194 | 2.2865 | 400 | 0.2177 | 0.956 | 0.9091 |
| 0.0165 | 2.5731 | 450 | 0.2319 | 0.962 | 0.9224 |
| 0.0507 | 2.8596 | 500 | 0.1857 | 0.956 | 0.9098 |
| 0.0393 | 3.1433 | 550 | 0.2356 | 0.954 | 0.9091 |
| 0.0057 | 3.4298 | 600 | 0.2623 | 0.952 | 0.9055 |
| 0.0114 | 3.7163 | 650 | 0.2037 | 0.962 | 0.9218 |
| 0.0011 | 4.0 | 700 | 0.2164 | 0.964 | 0.9268 |
| 0.0012 | 4.2865 | 750 | 0.2124 | 0.966 | 0.9289 |
| 0.0022 | 4.5731 | 800 | 0.2360 | 0.962 | 0.9237 |
| 0.0087 | 4.8596 | 850 | 0.2205 | 0.966 | 0.9306 |
| 0.0002 | 5.1433 | 900 | 0.2256 | 0.964 | 0.9268 |
| 0.0001 | 5.4298 | 950 | 0.2293 | 0.962 | 0.9231 |
| 0.0001 | 5.7163 | 1000 | 0.2312 | 0.962 | 0.9231 |
| 0.0001 | 6.0 | 1050 | 0.2318 | 0.962 | 0.9231 |
Framework versions
- Transformers 4.53.1
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Languages
- es
- Created
- Jul 12, 2025
- Updated
- Jul 12, 2025