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results_flausch_classification_gbert-large_comment
Wiebke/results_flausch_classification_gbert-large_comment
results_flausch_classification_gbert-large_comment is a text classification model from Wiebke. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- May 28, 2025
- Updated
- May 28, 2025
- SHA
- 809c5eb0
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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. -->
results_flausch_classification_gbert-large
This model is a fine-tuned version of deepset/gbert-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2125
- Accuracy: 0.9494
- F1: 0.9494
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: 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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.2764 | 0.2822 | 500 | 0.2419 | 0.9254 | 0.9260 |
| 0.2448 | 0.5643 | 1000 | 0.2027 | 0.9312 | 0.9314 |
| 0.2176 | 0.8465 | 1500 | 0.2286 | 0.9294 | 0.9274 |
| 0.1907 | 1.1287 | 2000 | 0.2143 | 0.9424 | 0.9421 |
| 0.165 | 1.4108 | 2500 | 0.1824 | 0.9448 | 0.9447 |
| 0.148 | 1.6930 | 3000 | 0.2112 | 0.9462 | 0.9460 |
| 0.1464 | 1.9752 | 3500 | 0.1738 | 0.9460 | 0.9461 |
| 0.0991 | 2.2573 | 4000 | 0.2521 | 0.9466 | 0.9465 |
| 0.1036 | 2.5395 | 4500 | 0.2269 | 0.9502 | 0.9501 |
| 0.107 | 2.8217 | 5000 | 0.2125 | 0.9494 | 0.9494 |
Framework versions
- Transformers 4.52.2
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- May 28, 2025
- Updated
- May 28, 2025