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bert-uncased-AG-News
bakanaims/bert-uncased-AG-News
bert-uncased-AG-News is a text classification model from bakanaims. 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
- bert
- Access
- Public
- Created
- Jun 10, 2024
- Updated
- Jun 10, 2024
- SHA
- 69282b0f
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Base models
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. -->
bert-uncased-AG-News
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7208
- Balanced Accuracy: 0.8720
- Accuracy: 0.8667
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- 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 | Balanced Accuracy | Accuracy |
|---|---|---|---|---|---|
| 1.3219 | 1.0 | 25 | 0.8636 | 0.7889 | 0.79 |
| 0.6342 | 2.0 | 50 | 0.5691 | 0.8689 | 0.86 |
| 0.2991 | 3.0 | 75 | 0.5546 | 0.8602 | 0.86 |
| 0.1403 | 4.0 | 100 | 0.6923 | 0.8719 | 0.8667 |
| 0.0561 | 5.0 | 125 | 0.7208 | 0.8720 | 0.8667 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jun 10, 2024
- Updated
- Jun 10, 2024