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Add fine-tuned ViSoBERT for hate speech detection
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---
library_name: transformers
base_model: uitnlp/visobert
tags:
- generated_from_trainer
model-index:
- name: hatespeech-multitask-vithsd
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hatespeech-multitask-vithsd
This model is a fine-tuned version of [uitnlp/visobert](https://huggingface.co/uitnlp/visobert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4582
- Hamming Loss: 0.104
- Subset Accuracy: 0.0
- Per Label Accuracy: 0.8960
- F1 Macro: 0.1837
- F1 Weighted: 0.6493
## 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
- 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_ratio: 0.1
- num_epochs: 1
### Training results
### Framework versions
- Transformers 4.57.6
- Pytorch 2.9.0+cpu
- Datasets 4.0.0
- Tokenizers 0.22.2