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zero-shot_text_classification_pre_trained
MaVier19/zero-shot_text_classification_pre_trained
zero-shot_text_classification_pre_trained is a text classification model from MaVier19. 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 6, 2024
- Updated
- Jan 6, 2024
- SHA
- 3d72a5d4
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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. -->
zero-shot_text_classification_pre_trained
This model is a fine-tuned version of MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8939
- Accuracy: 0.695
- F1: 0.6917
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- 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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.7346 | 1.0 | 750 | 0.8939 | 0.695 | 0.6917 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Jan 6, 2024
- Updated
- Jan 6, 2024