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homolat-beto-baseline
helenpy/homolat-beto-baseline
homolat-beto-baseline is a text classification model from helenpy. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Jul 3, 2025
- Updated
- Jul 3, 2025
- SHA
- 537fd70e
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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. -->
homolat-beto-baseline
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: 0.8615
- F1: 0.3633
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-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.96 | 1.0 | 721 | 0.8327 | 0.2540 |
| 0.955 | 2.0 | 1442 | 0.8465 | 0.2540 |
| 0.9413 | 3.0 | 2163 | 0.8615 | 0.3633 |
Framework versions
- Transformers 4.53.0
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Jul 3, 2025
- Updated
- Jul 3, 2025