jobBERT-de_tc_professions_debates
This model is a fine-tuned version of agne/jobBERT-de on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0581
- Precision: 0.9648
- Recall: 0.9481
- F1: 0.9564
- Accuracy: 0.9924
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 31 | 0.0394 | 0.9430 | 0.9538 | 0.9484 | 0.9909 |
| No log | 2.0 | 62 | 0.0462 | 0.9222 | 0.9577 | 0.9396 | 0.9897 |
| No log | 3.0 | 93 | 0.0556 | 0.9556 | 0.9519 | 0.9538 | 0.9919 |
| No log | 4.0 | 124 | 0.0604 | 0.9647 | 0.9462 | 0.9553 | 0.9924 |
| No log | 5.0 | 155 | 0.0581 | 0.9648 | 0.9481 | 0.9564 | 0.9924 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.13.3
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