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distilbert-base-uncased-distilled-clinc
xingguoli/distilbert-base-uncased-distilled-clinc
distilbert-base-uncased-distilled-clinc is a machine learning model from xingguoli. 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 26, 2024
- Updated
- Sep 26, 2024
- SHA
- 9a6840ba
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. -->
distilbert-base-uncased-distilled-clinc
This model is a fine-tuned version of distilbert-base-uncased on the clinc_oos dataset. It achieves the following results on the evaluation set:
- Loss: 0.0383
- Accuracy: 0.9287
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: 9
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.8117 | 1.0 | 318 | 0.4181 | 0.6635 |
| 0.3202 | 2.0 | 636 | 0.1500 | 0.8416 |
| 0.1495 | 3.0 | 954 | 0.0778 | 0.8990 |
| 0.0963 | 4.0 | 1272 | 0.0563 | 0.9129 |
| 0.0754 | 5.0 | 1590 | 0.0475 | 0.9206 |
| 0.0652 | 6.0 | 1908 | 0.0429 | 0.9258 |
| 0.0595 | 7.0 | 2226 | 0.0401 | 0.9297 |
| 0.0562 | 8.0 | 2544 | 0.0387 | 0.9277 |
| 0.0546 | 9.0 | 2862 | 0.0383 | 0.9287 |
Framework versions
- Transformers 4.16.2
- Pytorch 2.4.1+cu121
- Datasets 1.16.1
- Tokenizers 0.19.1
- Type
- distilbert
- License
- apache-2.0
- Created
- Sep 26, 2024
- Updated
- Sep 26, 2024