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hr_cate
tangminhanh/hr_cate
hr_cate is a text classification model from tangminhanh. 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-v2
- Access
- Public
- Created
- Jul 23, 2024
- Updated
- Jul 23, 2024
- SHA
- 2eaf2b39
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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. -->
hr_cate
This model is a fine-tuned version of microsoft/deberta-v3-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0404
- Accuracy: 0.7833
- F1: 0.8459
- Precision: 0.9146
- Recall: 0.7869
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-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
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 227 | 0.0946 | 0.4140 | 0.5702 | 0.9179 | 0.4136 |
| No log | 2.0 | 454 | 0.0573 | 0.6871 | 0.7845 | 0.9153 | 0.6864 |
| 0.1387 | 3.0 | 681 | 0.0468 | 0.7629 | 0.8291 | 0.9091 | 0.7620 |
| 0.1387 | 4.0 | 908 | 0.0420 | 0.7722 | 0.8372 | 0.9138 | 0.7725 |
| 0.0456 | 5.0 | 1135 | 0.0404 | 0.7833 | 0.8459 | 0.9146 | 0.7869 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Jul 23, 2024
- Updated
- Jul 23, 2024