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# banking77-text-classification

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1", "accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "banking77-text-classification", "results": []}]}
transformers tensorboard safetensors bert text-classification generated_from_trainer base_model:bert-base-uncased license:apache-2.0 autotrain_compatible endpoints_compatible region:us