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roberta-sst2-distilled
thewiz/roberta-sst2-distilled
roberta-sst2-distilled is a text classification model from thewiz. 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
- roberta
- Access
- Public
- Created
- Dec 6, 2023
- Updated
- Dec 6, 2023
- SHA
- ee61d374
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Base models
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. -->
roberta-sst2-distilled
This model is a fine-tuned version of roberta-base on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.2485
- Accuracy: 0.9300
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: 6e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 33
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.257 | 1.0 | 527 | 0.2575 | 0.9117 |
| 0.2386 | 2.0 | 1054 | 0.2469 | 0.9369 |
| 0.2331 | 3.0 | 1581 | 0.2484 | 0.9358 |
| 0.2289 | 4.0 | 2108 | 0.2516 | 0.9278 |
| 0.2266 | 5.0 | 2635 | 0.2499 | 0.9335 |
| 0.2252 | 6.0 | 3162 | 0.2477 | 0.9312 |
| 0.2238 | 7.0 | 3689 | 0.2485 | 0.9300 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Dec 6, 2023
- Updated
- Dec 6, 2023