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muril-adapted-local-FakeNews-Dravidian-muril
mdosama39/muril-adapted-local-FakeNews-Dravidian-muril
muril-adapted-local-FakeNews-Dravidian-muril is a text classification model from mdosama39. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Nov 22, 2023
- Updated
- Nov 22, 2023
- SHA
- 9b8be1ea
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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. -->
muril-adapted-local-FakeNews-Dravidian-muril
This model is a fine-tuned version of monsoon-nlp/muril-adapted-local on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5333
- Accuracy: 0.7448
- Weighted f1 score: 0.7448
- Macro f1 score: 0.7447
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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 score | Macro f1 score |
|---|---|---|---|---|---|---|
| 0.7193 | 1.0 | 204 | 0.7031 | 0.5350 | 0.4469 | 0.4477 |
| 0.6807 | 2.0 | 408 | 0.6694 | 0.5840 | 0.5800 | 0.5798 |
| 0.6606 | 3.0 | 612 | 0.6487 | 0.6160 | 0.6160 | 0.6160 |
| 0.6377 | 4.0 | 816 | 0.6211 | 0.6638 | 0.6602 | 0.6601 |
| 0.5906 | 5.0 | 1020 | 0.6154 | 0.6748 | 0.6552 | 0.6549 |
| 0.5526 | 6.0 | 1224 | 0.5716 | 0.6994 | 0.6956 | 0.6955 |
| 0.5195 | 7.0 | 1428 | 0.5471 | 0.7202 | 0.7200 | 0.7199 |
| 0.4945 | 8.0 | 1632 | 0.5410 | 0.7264 | 0.7256 | 0.7255 |
| 0.4635 | 9.0 | 1836 | 0.5448 | 0.7350 | 0.7332 | 0.7332 |
| 0.4453 | 10.0 | 2040 | 0.5355 | 0.7362 | 0.7358 | 0.7358 |
| 0.429 | 11.0 | 2244 | 0.5337 | 0.7362 | 0.7356 | 0.7356 |
| 0.4262 | 12.0 | 2448 | 0.5539 | 0.7399 | 0.7374 | 0.7373 |
| 0.4041 | 13.0 | 2652 | 0.5334 | 0.7485 | 0.7484 | 0.7484 |
| 0.3983 | 14.0 | 2856 | 0.5326 | 0.7497 | 0.7497 | 0.7497 |
| 0.3798 | 15.0 | 3060 | 0.5333 | 0.7448 | 0.7448 | 0.7447 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.14.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Nov 22, 2023
- Updated
- Nov 22, 2023