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# whatsapp-group-classifier

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6423
- Accuracy: 0.8605
- Precision: 0.8759
- Recall: 0.8691
- F1: 0.8723

## 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: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.5825        | 1.0   | 513  | 0.4116          | 0.8424   | 0.8689    | 0.8456 | 0.8548 |
| 0.3391        | 2.0   | 1026 | 0.3898          | 0.8551   | 0.8757    | 0.8657 | 0.8694 |
| 0.2476        | 3.0   | 1539 | 0.4915          | 0.8532   | 0.8659    | 0.8628 | 0.8641 |
| 0.1637        | 4.0   | 2052 | 0.5531          | 0.8556   | 0.8733    | 0.8671 | 0.8694 |
| 0.1173        | 5.0   | 2565 | 0.6423          | 0.8605   | 0.8759    | 0.8691 | 0.8723 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy", "precision", "recall", "f1"], "base_model": "bert-base-uncased", "model-index": [{"name": "whatsapp-group-classifier", "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