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domain_classification
phongmt184172/domain_classification
domain_classification is a text classification model from phongmt184172. 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
- distilbert
- Access
- Public
- Created
- Jul 17, 2023
- Updated
- Jul 17, 2023
- SHA
- 0541ffd9
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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. -->
Domain classification model
This model is a fine-tuned version of distilbert-base-uncased on the Opus dataset with IT, medical, law domain.They are extracted from OPUS dataset in english. It achieves the following results on the evaluation set:
- Loss: 0.1140
- Accuracy: 0.9750
Model description
The model will classify sentence which belongs to its domain.
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.13 | 1.0 | 2838 | 0.1201 | 0.9691 |
| 0.0609 | 2.0 | 5676 | 0.1140 | 0.9750 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jul 17, 2023
- Updated
- Jul 17, 2023