Instructions to use raul-jimenez8-uclm/results_hate_speech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use raul-jimenez8-uclm/results_hate_speech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="raul-jimenez8-uclm/results_hate_speech")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("raul-jimenez8-uclm/results_hate_speech") model = AutoModelForSequenceClassification.from_pretrained("raul-jimenez8-uclm/results_hate_speech") - Notebooks
- Google Colab
- Kaggle
results_hate_speech
This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3914
- Accuracy: 0.85
- F1: 0.4079
- Precision: 0.5536
- Recall: 0.3229
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: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4025 | 1.0 | 188 | 0.4087 | 0.845 | 0.0792 | 0.8 | 0.0417 |
| 0.2873 | 2.0 | 376 | 0.3914 | 0.85 | 0.4079 | 0.5536 | 0.3229 |
| 0.1733 | 3.0 | 564 | 0.5351 | 0.8283 | 0.4046 | 0.4545 | 0.3646 |
Framework versions
- Transformers 5.9.0
- Pytorch 2.11.0+cpu
- Datasets 4.8.5
- Tokenizers 0.22.2
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Model tree for raul-jimenez8-uclm/results_hate_speech
Base model
dccuchile/bert-base-spanish-wwm-cased