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# job-salary-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: 0.2494
- F1: 0.6873
- Roc Auc: 0.8006
- Accuracy: 0.6494

## 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: 7

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 39   | 0.3015          | 0.4057 | 0.6299  | 0.2792   |
| No log        | 2.0   | 78   | 0.2932          | 0.5674 | 0.7286  | 0.5195   |
| No log        | 3.0   | 117  | 0.2666          | 0.6494 | 0.7669  | 0.5714   |
| No log        | 4.0   | 156  | 0.2524          | 0.7010 | 0.8084  | 0.6623   |
| No log        | 5.0   | 195  | 0.2509          | 0.6990 | 0.8058  | 0.6558   |
| No log        | 6.0   | 234  | 0.2497          | 0.7103 | 0.8130  | 0.6688   |
| No log        | 7.0   | 273  | 0.2494          | 0.6873 | 0.8006  | 0.6494   |


### 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": ["f1", "accuracy"], "base_model": "bert-base-uncased", "model-index": [{"name": "job-salary-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