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roberta-hate-speech-olid
ARC4N3/roberta-hate-speech-olid
roberta-hate-speech-olid is a text classification model from ARC4N3. 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
- roberta
- Access
- Public
- Created
- Mar 3, 2024
- Updated
- Mar 3, 2024
- SHA
- 78074bc0
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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. -->
experiment-model-roberta
This model is a fine-tuned version of facebook/roberta-hate-speech-dynabench-r4-target on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6733
- Accuracy: 0.8538
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3299 | 1.0 | 884 | 0.3470 | 0.8453 |
| 0.3061 | 2.0 | 1768 | 0.3472 | 0.8546 |
| 0.2706 | 3.0 | 2652 | 0.3926 | 0.8583 |
| 0.1706 | 4.0 | 3536 | 0.5401 | 0.8495 |
| 0.1454 | 5.0 | 4420 | 0.6733 | 0.8538 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Mar 3, 2024
- Updated
- Mar 3, 2024