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FakeNews-deberta-large-grad
Denyol/FakeNews-deberta-large-grad
FakeNews-deberta-large-grad is a text classification model from Denyol. 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
- deberta
- Access
- Public
- Created
- Nov 7, 2023
- Updated
- Nov 7, 2023
- SHA
- 2694965e
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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. -->
FakeNews-deberta-large-grad
This model is a fine-tuned version of microsoft/deberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4159
- Accuracy: 0.8547
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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 |
|---|---|---|---|---|
| 0.5255 | 1.0 | 802 | 0.4159 | 0.8547 |
| 0.4852 | 2.0 | 1605 | 0.4894 | 0.7631 |
| 0.4849 | 3.0 | 2407 | 0.4670 | 0.7710 |
| 0.4839 | 4.0 | 3210 | 0.4664 | 0.7729 |
| 0.5581 | 5.0 | 4010 | 0.7548 | 0.4766 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Text Classification
- Library
- transformers
- Type
- deberta
- License
- mit
- Created
- Nov 7, 2023
- Updated
- Nov 7, 2023