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roberta-news-classifier
resul-ai/roberta-news-classifier
roberta-news-classifier is a text classification model from resul-ai. 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
- roberta
- Access
- Public
- Created
- Dec 1, 2022
- Updated
- Dec 4, 2022
- SHA
- 21557791
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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. -->
roberta-news-classifier
This model is a fine-tuned version of russellc/roberta-news-classifier on the custom(Kaggle) dataset. It achieves the following results on the evaluation set:
- Loss: 0.1043
- Accuracy: 0.9786
- F1: 0.9786
- Precision: 0.9786
- Recall: 0.9786
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.1327 | 1.0 | 123 | 0.1043 | 0.9786 | 0.9786 | 0.9786 | 0.9786 |
| 0.1103 | 2.0 | 246 | 0.1157 | 0.9735 | 0.9735 | 0.9735 | 0.9735 |
| 0.102 | 3.0 | 369 | 0.1104 | 0.9735 | 0.9735 | 0.9735 | 0.9735 |
| 0.0825 | 4.0 | 492 | 0.1271 | 0.9714 | 0.9714 | 0.9714 | 0.9714 |
| 0.055 | 5.0 | 615 | 0.1296 | 0.9724 | 0.9724 | 0.9724 | 0.9724 |
Evaluation results
***** Running Prediction *****
Num examples = 980
Batch size = 64
precision recall f1-score support
dunya 0.99 0.96 0.97 147
ekonomi 0.96 0.96 0.96 141
kultur 0.97 0.99 0.98 142
saglik 0.99 0.98 0.98 148
siyaset 0.98 0.98 0.98 134
spor 1.00 1.00 1.00 139
teknoloji 0.96 0.98 0.97 129
accuracy -- -- 0.98 980
macro avg 0.98 0.98 0.98 980
weighted avg 0.98 0.98 0.98 980
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Dec 1, 2022
- Updated
- Dec 4, 2022