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deberta_base_fine_tune_mnli_half_v1
grace-pro/deberta_base_fine_tune_mnli_half_v1
deberta_base_fine_tune_mnli_half_v1 is a text classification model from grace-pro. 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 1, 2024
- Updated
- Jan 1, 2024
- SHA
- 6e03bb73
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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_base_fine_tune_mnli_half_v1
This model is a fine-tuned version of microsoft/deberta-v3-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3669
- Accuracy: 0.8993
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: 32
- 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 | Accuracy |
|---|---|---|---|---|
| 0.3187 | 1.0 | 6136 | 0.2787 | 0.8963 |
| 0.2211 | 2.0 | 12272 | 0.3036 | 0.9002 |
| 0.1372 | 3.0 | 18408 | 0.3669 | 0.8993 |
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 1, 2024
- Updated
- Jan 1, 2024