Downloads · 30 days
10
3% of all-time downloads
FakeNews-roberta-base
Denyol/FakeNews-roberta-base
FakeNews-roberta-base 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. --
All-time downloads
304
Public
Repo size
3 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin499 MB · 99%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Oct 21, 2023
- Updated
- Oct 21, 2023
- SHA
- e03688e4
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. -->
FakeNews-roberta-base
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0956
- Accuracy: 0.9804
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: 8
- eval_batch_size: 8
- seed: 42
- 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 |
|---|---|---|---|---|
| 0.3357 | 1.0 | 803 | 0.2511 | 0.9458 |
| 0.1162 | 2.0 | 1606 | 0.1605 | 0.9682 |
| 0.0615 | 3.0 | 2409 | 0.0956 | 0.9804 |
| 0.0285 | 4.0 | 3212 | 0.1915 | 0.9720 |
| 0.0098 | 5.0 | 4015 | 0.1241 | 0.9827 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Oct 21, 2023
- Updated
- Oct 21, 2023