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heladepdet-bert-finetuned-classification
tadamaen/heladepdet-bert-finetuned-classification
heladepdet-bert-finetuned-classification is a machine learning model from tadamaen. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. 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
- Library
- peft
- License
- apache-2.0
- Access
- Public
- Created
- Mar 31, 2026
- Updated
- Apr 2, 2026
- SHA
- 5a30e5e7
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. -->
<a href="https://huggingface.co/spaces/tadamaen/bert-model-dsa4262" target="_blank"><img src="https://raw.githubusercontent.com/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in Trackio" title="Visualize in Trackio" style="height: 40px;"/></a>
heladepdet-bert-finetuned-classification
This model is a fine-tuned version of google-bert/bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2607
- Accuracy: 0.7084
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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 |
|---|---|---|---|---|
| 2.5972 | 0.5734 | 250 | 2.1673 | 0.5408 |
| 1.8338 | 1.1468 | 500 | 1.5411 | 0.6361 |
| 1.5037 | 1.7202 | 750 | 1.4124 | 0.6670 |
| 1.4176 | 2.2936 | 1000 | 1.3331 | 0.6871 |
| 1.3283 | 2.8670 | 1250 | 1.3027 | 0.6969 |
| 1.3123 | 3.4404 | 1500 | 1.2863 | 0.6940 |
| 1.2613 | 4.0138 | 1750 | 1.2653 | 0.7067 |
| 1.2477 | 4.5872 | 2000 | 1.2607 | 0.7084 |
Framework versions
- PEFT 0.18.1
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
- Library
- peft
- License
- apache-2.0
- Created
- Mar 31, 2026
- Updated
- Apr 2, 2026