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gpt2-hatexplain
uboza10300/gpt2-hatexplain
gpt2-hatexplain is a text classification model from uboza10300. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- gpt2
- Access
- Public
- Created
- Dec 10, 2024
- Updated
- Dec 10, 2024
- SHA
- e68d6feb
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Base models
Datasets
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. -->
gpt2-hatexplain
This model is a fine-tuned version of gpt2 on the hatexplain dataset. It achieves the following results on the evaluation set:
- Loss: 0.7507
- Accuracy: 0.6918
- Precision: 0.6838
- Recall: 0.6918
- F1: 0.6822
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: 16
- 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
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.7396 | 1.0 | 962 | 0.7567 | 0.6790 | 0.6713 | 0.6790 | 0.6641 |
| 0.6697 | 2.0 | 1924 | 0.7486 | 0.6842 | 0.6769 | 0.6842 | 0.6783 |
| 0.7573 | 3.0 | 2886 | 0.7685 | 0.6748 | 0.6658 | 0.6748 | 0.6656 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- gpt2
- License
- mit
- Created
- Dec 10, 2024
- Updated
- Dec 10, 2024