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distilbert-base-uncased-finetuned-qnli
anuj55/distilbert-base-uncased-finetuned-qnli
distilbert-base-uncased-finetuned-qnli is a text classification model from anuj55. 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
- Mar 7, 2023
- Updated
- Mar 7, 2023
- SHA
- fde200db
Try a prompt
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-qnli
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.7416
- Accuracy: 0.2781
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|
| 1.738 | 1.0 | 635 | 1.7130 | 0.2656 |
| 1.671 | 2.0 | 1270 | 1.7190 | 0.2445 |
| 1.5906 | 3.0 | 1905 | 1.7416 | 0.2781 |
| 1.3229 | 4.0 | 2540 | 1.8047 | 0.2781 |
| 1.217 | 5.0 | 3175 | 1.8409 | 0.2773 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Mar 7, 2023
- Updated
- Mar 7, 2023