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distilbert-base-uncased-finetuned-cola-Christianity
bblackwell/distilbert-base-uncased-finetuned-cola-Christianity
distilbert-base-uncased-finetuned-cola-Christianity is a text classification model from bblackwell. 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
- Apr 12, 2023
- Updated
- Apr 25, 2023
- SHA
- ddfa19da
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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-cola-Christianity
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: 0.2016
- Matthews Correlation: 0.8950
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 | Matthews Correlation |
|---|---|---|---|---|
| 0.2197 | 1.0 | 615 | 0.1455 | 0.8815 |
| 0.13 | 2.0 | 1230 | 0.1453 | 0.8853 |
| 0.0859 | 3.0 | 1845 | 0.1854 | 0.8879 |
| 0.0511 | 4.0 | 2460 | 0.2016 | 0.8950 |
| 0.0183 | 5.0 | 3075 | 0.2132 | 0.8940 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Apr 12, 2023
- Updated
- Apr 25, 2023