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distilbert-base-uncased-finetuned-clinc
Jay-C/distilbert-base-uncased-finetuned-clinc
distilbert-base-uncased-finetuned-clinc is a text classification model from Jay-C. 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
- Oct 30, 2023
- Updated
- Oct 30, 2023
- SHA
- 90727613
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Base models
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-finetuned-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: 3.7475
- Accuracy: 0.6977
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: 384
- eval_batch_size: 384
- 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 | 40 | 4.7512 | 0.1526 |
| No log | 2.0 | 80 | 4.3202 | 0.5113 |
| No log | 3.0 | 120 | 4.0009 | 0.6310 |
| No log | 4.0 | 160 | 3.8111 | 0.68 |
| No log | 5.0 | 200 | 3.7475 | 0.6977 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Oct 30, 2023
- Updated
- Oct 30, 2023