wage_prediction
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3221
- Mse: -0.3221
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 32
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Mse |
|---|---|---|---|---|
| No log | 1.0 | 18 | 43.7387 | -43.7387 |
| No log | 2.0 | 36 | 22.7879 | -22.7879 |
| No log | 3.0 | 54 | 12.8629 | -12.8629 |
| No log | 4.0 | 72 | 6.6085 | -6.6085 |
| No log | 5.0 | 90 | 2.5628 | -2.5628 |
| No log | 6.0 | 108 | 0.6254 | -0.6254 |
| No log | 7.0 | 126 | 0.4496 | -0.4496 |
| No log | 8.0 | 144 | 0.5790 | -0.5790 |
| No log | 9.0 | 162 | 0.4185 | -0.4185 |
| No log | 10.0 | 180 | 0.5515 | -0.5515 |
| No log | 11.0 | 198 | 0.4093 | -0.4093 |
| No log | 12.0 | 216 | 0.3644 | -0.3644 |
| No log | 13.0 | 234 | 0.4353 | -0.4353 |
| No log | 14.0 | 252 | 0.3436 | -0.3436 |
| No log | 15.0 | 270 | 0.3732 | -0.3732 |
| No log | 16.0 | 288 | 0.3497 | -0.3497 |
| No log | 17.0 | 306 | 0.4740 | -0.4740 |
| No log | 18.0 | 324 | 0.3512 | -0.3512 |
| No log | 19.0 | 342 | 0.3436 | -0.3436 |
| No log | 20.0 | 360 | 0.3857 | -0.3857 |
| No log | 21.0 | 378 | 0.3253 | -0.3253 |
| No log | 22.0 | 396 | 0.3281 | -0.3281 |
| No log | 23.0 | 414 | 0.3349 | -0.3349 |
| No log | 24.0 | 432 | 0.3329 | -0.3329 |
| No log | 25.0 | 450 | 0.3280 | -0.3280 |
| No log | 26.0 | 468 | 0.3268 | -0.3268 |
| No log | 27.0 | 486 | 0.3205 | -0.3205 |
| 5.0934 | 28.0 | 504 | 0.3351 | -0.3351 |
| 5.0934 | 29.0 | 522 | 0.3283 | -0.3283 |
| 5.0934 | 30.0 | 540 | 0.3193 | -0.3193 |
| 5.0934 | 31.0 | 558 | 0.3204 | -0.3204 |
| 5.0934 | 32.0 | 576 | 0.3221 | -0.3221 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1