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distilbert-base-uncased-finetuned-clinc
h1nadesu/distilbert-base-uncased-finetuned-clinc
distilbert-base-uncased-finetuned-clinc is a machine learning model from h1nadesu. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Jul 14, 2026
- Updated
- Jul 15, 2026
- SHA
- a22b2cb8
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-finetuned-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: 0.7952
- Accuracy: 0.9197
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: 48
- eval_batch_size: 48
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 318 | 3.3170 | 0.7406 |
| 3.8192 | 2.0 | 636 | 1.9067 | 0.8497 |
| 3.8192 | 3.0 | 954 | 1.1836 | 0.8945 |
| 1.7292 | 4.0 | 1272 | 0.8785 | 0.9142 |
| 0.926 | 5.0 | 1590 | 0.7952 | 0.9197 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.11.0+cu128
- Datasets 2.14.7
- Tokenizers 0.15.2
- Type
- distilbert
- License
- apache-2.0
- Created
- Jul 14, 2026
- Updated
- Jul 15, 2026