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bert-base-swedish-cased-new-finetuned-augmentation
sercetexam9/bert-base-swedish-cased-new-finetuned-augmentation
bert-base-swedish-cased-new-finetuned-augmentation is a text classification model from sercetexam9. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Jan 29, 2025
- Updated
- Jan 29, 2025
- SHA
- 3e8d6730
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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-base-swedish-cased-new-finetuned-augmentation
This model is a fine-tuned version of KBLab/bert-base-swedish-cased-new on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1896
- F1: 0.5215
- Roc Auc: 0.7532
- Accuracy: 0.6931
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: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.4332 | 1.0 | 70 | 0.3604 | 0.1123 | 0.5414 | 0.4513 |
| 0.2766 | 2.0 | 140 | 0.2395 | 0.3940 | 0.6846 | 0.6606 |
| 0.2381 | 3.0 | 210 | 0.2095 | 0.3914 | 0.6785 | 0.6606 |
| 0.2096 | 4.0 | 280 | 0.2080 | 0.4761 | 0.7219 | 0.6751 |
| 0.186 | 5.0 | 350 | 0.2017 | 0.4803 | 0.7216 | 0.6570 |
| 0.1801 | 6.0 | 420 | 0.1937 | 0.4888 | 0.7343 | 0.6823 |
| 0.1333 | 7.0 | 490 | 0.1935 | 0.4903 | 0.7354 | 0.6606 |
| 0.1128 | 8.0 | 560 | 0.1962 | 0.4930 | 0.7356 | 0.6823 |
| 0.1107 | 9.0 | 630 | 0.2039 | 0.5069 | 0.7467 | 0.6643 |
| 0.0909 | 10.0 | 700 | 0.1896 | 0.5215 | 0.7532 | 0.6931 |
| 0.0811 | 11.0 | 770 | 0.2059 | 0.5147 | 0.7571 | 0.6679 |
| 0.0762 | 12.0 | 840 | 0.1988 | 0.5052 | 0.7423 | 0.6715 |
| 0.0673 | 13.0 | 910 | 0.1984 | 0.5160 | 0.7416 | 0.6968 |
| 0.0482 | 14.0 | 980 | 0.2044 | 0.5050 | 0.7430 | 0.6679 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Created
- Jan 29, 2025
- Updated
- Jan 29, 2025