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distilbert-base-uncased-qa-boolq
andi611/distilbert-base-uncased-qa-boolq
distilbert-base-uncased-qa-boolq is a text classification model from andi611. 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 2, 2022
- Updated
- Aug 2, 2021
- SHA
- 168ef095
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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-boolq
This model is a fine-tuned version of distilbert-base-uncased on the boolq dataset. It achieves the following results on the evaluation set:
- Loss: 1.2071
- Accuracy: 0.7315
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6506 | 1.0 | 531 | 0.6075 | 0.6681 |
| 0.575 | 2.0 | 1062 | 0.5816 | 0.6978 |
| 0.4397 | 3.0 | 1593 | 0.6137 | 0.7253 |
| 0.2524 | 4.0 | 2124 | 0.8124 | 0.7466 |
| 0.126 | 5.0 | 2655 | 1.1437 | 0.7370 |
Framework versions
- Transformers 4.8.2
- Pytorch 1.8.1+cu111
- Datasets 1.8.0
- Tokenizers 0.10.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Aug 2, 2021