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deberta-v3-smallsed_rte-finetuned-rte
ZaaCo/deberta-v3-smallsed_rte-finetuned-rte
deberta-v3-smallsed_rte-finetuned-rte is a text classification model from ZaaCo. 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
- Mar 5, 2024
- Updated
- Mar 5, 2024
- SHA
- 93c0f851
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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. -->
deberta-v3-smallsed_rte-finetuned-rte
This model is a fine-tuned version of microsoft/deberta-v3-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6608
- Accuracy: 0.7148
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: 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 156 | 0.6549 | 0.6354 |
| No log | 2.0 | 312 | 0.5761 | 0.7040 |
| No log | 3.0 | 468 | 0.6608 | 0.7148 |
| 0.5162 | 4.0 | 624 | 0.9686 | 0.7076 |
| 0.5162 | 5.0 | 780 | 1.1002 | 0.7040 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Mar 5, 2024
- Updated
- Mar 5, 2024