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# bert-base-uncased-Adult-Text-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: 0.1257
- Accuracy: 0.9824

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 43   | 0.1197          | 0.9588   |
| No log        | 2.0   | 86   | 0.1943          | 0.9529   |
| No log        | 3.0   | 129  | 0.0942          | 0.9765   |
| No log        | 4.0   | 172  | 0.1308          | 0.9765   |
| No log        | 5.0   | 215  | 0.1178          | 0.9765   |
| No log        | 6.0   | 258  | 0.1159          | 0.9824   |
| No log        | 7.0   | 301  | 0.1175          | 0.9824   |
| No log        | 8.0   | 344  | 0.1209          | 0.9824   |
| No log        | 9.0   | 387  | 0.1243          | 0.9824   |
| No log        | 10.0  | 430  | 0.1257          | 0.9824   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "bert-base-uncased-Adult-Text-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