banking77-text-classification
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4686
- F1: 0.8989
- Accuracy: 0.9054
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
|---|---|---|---|---|---|
| 3.9638 | 0.46 | 100 | 3.1616 | 0.3449 | 0.4205 |
| 2.5608 | 0.91 | 200 | 1.9064 | 0.6739 | 0.7231 |
| 1.5807 | 1.37 | 300 | 1.2332 | 0.7769 | 0.8111 |
| 1.0547 | 1.83 | 400 | 0.8750 | 0.8433 | 0.8594 |
| 0.7201 | 2.28 | 500 | 0.6806 | 0.8620 | 0.8777 |
| 0.5474 | 2.74 | 600 | 0.5627 | 0.8856 | 0.8970 |
| 0.4168 | 3.2 | 700 | 0.5010 | 0.8884 | 0.8984 |
| 0.3382 | 3.65 | 800 | 0.4686 | 0.8989 | 0.9054 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
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Model tree for ramnathv/banking77-text-classification
Base model
google-bert/bert-base-uncased