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bert-amazon-classifier
rishi19/bert-amazon-classifier
bert-amazon-classifier is a text classification model from rishi19. 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
- Feb 22, 2026
- Updated
- Feb 22, 2026
- SHA
- ba2c1ccb
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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-amazon-classifier
This model is a fine-tuned version of google-bert/bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6907
- Accuracy: 0.6
- F1 Macro: 0.375
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: 0.0002
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro |
|---|---|---|---|---|---|
| 2.8146 | 1.0 | 11 | 2.1776 | 0.4 | 0.2667 |
| 2.2618 | 2.0 | 22 | 1.9192 | 0.6 | 0.375 |
| 2.1497 | 3.0 | 33 | 1.7641 | 0.6 | 0.375 |
| 2.0477 | 4.0 | 44 | 1.7136 | 0.6 | 0.375 |
| 2.0122 | 5.0 | 55 | 1.6907 | 0.6 | 0.375 |
Framework versions
- Transformers 4.54.0.dev0
- Pytorch 2.7.1
- Datasets 4.0.0
- Tokenizers 0.21.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Feb 22, 2026
- Updated
- Feb 22, 2026