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distilbert-base-uncased-finetuned-clinc
NobuA/distilbert-base-uncased-finetuned-clinc
distilbert-base-uncased-finetuned-clinc is a machine learning model from NobuA. 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
- Sep 8, 2024
- Updated
- Sep 9, 2024
- SHA
- 2b34c854
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: 0.8016
- Accuracy: 0.9177
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 318 | 3.3032 | 0.7171 |
| 3.8072 | 2.0 | 636 | 1.9041 | 0.8445 |
| 3.8072 | 3.0 | 954 | 1.1864 | 0.8884 |
| 1.7326 | 4.0 | 1272 | 0.8879 | 0.9119 |
| 0.9355 | 5.0 | 1590 | 0.8016 | 0.9177 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- distilbert
- License
- apache-2.0
- Created
- Sep 8, 2024
- Updated
- Sep 9, 2024