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mdeberta-v3-base-vsfc-100
tmnam20/mdeberta-v3-base-vsfc-100
mdeberta-v3-base-vsfc-100 is a text classification model from tmnam20. 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
- Jan 16, 2024
- Updated
- Jan 16, 2024
- SHA
- eff624a7
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Base models
Datasets
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. -->
mdeberta-v3-base-vsfc-100
This model is a fine-tuned version of microsoft/mdeberta-v3-base on the tmnam20/VieGLUE/VSFC dataset. It achieves the following results on the evaluation set:
- Loss: 0.2290
- Accuracy: 0.9457
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: 16
- seed: 100
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.1763 | 1.4 | 500 | 0.2099 | 0.9431 |
| 0.1363 | 2.79 | 1000 | 0.2278 | 0.9463 |
Framework versions
- Transformers 4.36.0
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Languages
- en
- Created
- Jan 16, 2024
- Updated
- Jan 16, 2024