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distilbert-base-uncased-ft-clinc
liuguojing/distilbert-base-uncased-ft-clinc
distilbert-base-uncased-ft-clinc is a text classification model from liuguojing. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Jul 5, 2024
- Updated
- Jul 5, 2024
- SHA
- 9e6376d3
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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. -->
distilbert-base-uncased-ft-clinc
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5254
- Accuracy: 0.8310
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: 0.0003
- 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 |
|---|---|---|---|---|
| 2.6686 | 1.0 | 239 | 2.0599 | 0.1635 |
| 1.6511 | 2.0 | 478 | 1.2657 | 0.4545 |
| 0.9693 | 3.0 | 717 | 0.8114 | 0.6571 |
| 0.6077 | 4.0 | 956 | 0.5993 | 0.7810 |
| 0.4334 | 5.0 | 1195 | 0.5254 | 0.8310 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.0.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jul 5, 2024
- Updated
- Jul 5, 2024