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roberta-large-finetuned-clinc
optimum/roberta-large-finetuned-clinc
roberta-large-finetuned-clinc is a text classification model from optimum. 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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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-large-finetuned-clinc
This model is a fine-tuned version of roberta-large on the clinc_oos dataset. It achieves the following results on the evaluation set:
- Loss: 0.1574
- Accuracy: 0.9729
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: 64
- eval_batch_size: 64
- 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 | 239 | 0.8113 | 0.9035 |
| No log | 2.0 | 478 | 0.2364 | 0.9548 |
| 1.7328 | 3.0 | 717 | 0.1760 | 0.9684 |
| 1.7328 | 4.0 | 956 | 0.1565 | 0.9723 |
| 0.0976 | 5.0 | 1195 | 0.1574 | 0.9729 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.11.0
- Datasets 1.16.1
- Tokenizers 0.10.3
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Apr 11, 2022
- Updated
- Jun 21, 2023