distilbert-base-uncased-finetuned-recruitment-exp
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1742
- Precision: 0.6204
- Recall: 0.6855
- F1: 0.6513
- Accuracy: 0.9561
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: 5e-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 | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 17 | 0.5203 | 0.0 | 0.0 | 0.0 | 0.8991 |
| No log | 2.0 | 34 | 0.3797 | 0.2979 | 0.0277 | 0.0507 | 0.9030 |
| No log | 3.0 | 51 | 0.2983 | 0.3171 | 0.4194 | 0.3612 | 0.9222 |
| No log | 4.0 | 68 | 0.2321 | 0.4219 | 0.4916 | 0.4541 | 0.9375 |
| No log | 5.0 | 85 | 0.2100 | 0.5076 | 0.5262 | 0.5168 | 0.9453 |
| No log | 6.0 | 102 | 0.1899 | 0.5174 | 0.5885 | 0.5507 | 0.9506 |
| No log | 7.0 | 119 | 0.1775 | 0.5395 | 0.6350 | 0.5834 | 0.9509 |
| No log | 8.0 | 136 | 0.1817 | 0.6282 | 0.6617 | 0.6445 | 0.9550 |
| No log | 9.0 | 153 | 0.1775 | 0.6262 | 0.6726 | 0.6485 | 0.9558 |
| No log | 10.0 | 170 | 0.1742 | 0.6204 | 0.6855 | 0.6513 | 0.9561 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3