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deberta-finetuned-answer-polarity-7e6
GCopoulos/deberta-finetuned-answer-polarity-7e6
deberta-finetuned-answer-polarity-7e6 is a text classification model from GCopoulos. 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
- Access
- Public
- Created
- Jun 2, 2023
- Updated
- Jun 2, 2023
- SHA
- 4b1d07a7
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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. -->
deberta-finetuned-answer-polarity-7e6
This model is a fine-tuned version of microsoft/deberta-large on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.9143
- F1: 0.8625
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: 7e-06
- 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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 214 | 0.6748 | 0.8696 |
| 0.0795 | 2.0 | 428 | 0.8541 | 0.8512 |
| 0.0508 | 3.0 | 642 | 0.9143 | 0.8625 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- deberta
- License
- mit
- Created
- Jun 2, 2023
- Updated
- Jun 2, 2023