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dignity-classifier-base
edmundmills/dignity-classifier-base
dignity-classifier-base is a text classification model from edmundmills. 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
- Jun 8, 2023
- Updated
- Aug 2, 2023
- SHA
- bf53fd01
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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. -->
dignity-classifier-base
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: 0.6340
- Accuracy: 0.8391
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: 32
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|
| 0.7117 | 1.0 | 98 | 0.6658 | 0.7328 |
| 0.4678 | 2.0 | 196 | 0.5435 | 0.7816 |
| 0.2648 | 3.0 | 294 | 0.5548 | 0.8132 |
| 0.1378 | 4.0 | 392 | 0.5295 | 0.8362 |
| 0.0561 | 5.0 | 490 | 0.6340 | 0.8391 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Jun 8, 2023
- Updated
- Aug 2, 2023