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xlm-roberta-base-finetuned-for-counterspeech-classification
abubakar-muhammad/xlm-roberta-base-finetuned-for-counterspeech-classification
xlm-roberta-base-finetuned-for-counterspeech-classification is a text classification model from abubakar-muhammad. 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
- xlm-roberta
- Access
- Public
- Created
- Mar 16, 2025
- Updated
- Mar 16, 2025
- SHA
- 4f553bef
Try a prompt
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. -->
results
This model is a fine-tuned version of cardiffnlp/twitter-xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0439
- Accuracy: 0.9918
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: 32
- eval_batch_size: 32
- 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
- lr_scheduler_warmup_steps: 100
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.0336 | 1.0 | 1617 | 0.0633 | 0.9867 |
| 0.0015 | 2.0 | 3234 | 0.0439 | 0.9918 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- Created
- Mar 16, 2025
- Updated
- Mar 16, 2025