job-salary-classifier
This model is a fine-tuned version of 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
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Base model
google-bert/bert-base-uncased