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hate_speech_recognition_model_lvd
LVitaD/hate_speech_recognition_model_lvd
hate_speech_recognition_model_lvd is a text classification model from LVitaD. 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
- Dec 7, 2025
- Updated
- Dec 7, 2025
- SHA
- fd0ba1f1
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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. -->
hate_speech_recognition_model_lvd
This model is a fine-tuned version of distilbert/distilroberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3397
- Accuracy: {'accuracy': 0.8557281553398058}
- F1: {'f1': 0.72015065913371}
- Precision: {'precision': 0.750392464678179}
- Recall: {'recall': 0.6922519913106444}
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: 32
- 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
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.3451 | 1.0 | 10139 | 0.3402 | {'accuracy': 0.8516782246879334} | {'f1': 0.7062894809118374} | {'precision': 0.7529866479269149} | {'recall': 0.6650460328954174} |
| 0.2948 | 2.0 | 20278 | 0.3397 | {'accuracy': 0.8557281553398058} | {'f1': 0.72015065913371} | {'precision': 0.750392464678179} | {'recall': 0.6922519913106444} |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- apache-2.0
- Created
- Dec 7, 2025
- Updated
- Dec 7, 2025