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bert-finetuned
miona-dimic/bert-finetuned
bert-finetuned is a text classification model from miona-dimic. 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
- May 6, 2024
- Updated
- May 6, 2024
- SHA
- 1511b8fd
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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-finetuned
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: 0.4578
- F1: 0.8667
- Roc Auc: 0.9
- 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: 2e-05
- train_batch_size: 3
- eval_batch_size: 3
- 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 | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.0805 | 1.0 | 6461 | 0.4578 | 0.8667 | 0.9 | 0.8667 |
| 0.0545 | 2.0 | 12922 | 0.7207 | 0.85 | 0.8875 | 0.85 |
| 0.0033 | 3.0 | 19383 | 0.9910 | 0.7395 | 0.8042 | 0.7333 |
| 0.0137 | 4.0 | 25844 | 1.1234 | 0.7731 | 0.8292 | 0.7667 |
| 0.0028 | 5.0 | 32305 | 1.1960 | 0.7731 | 0.8292 | 0.7667 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- May 6, 2024
- Updated
- May 6, 2024