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NLP-HIBA_DisTEMIST_fine_tuned_bert-base-multilingual-cased
This model is a fine-tuned version of bert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2057
- Precision: 0.6288
- Recall: 0.5579
- F1: 0.5912
- Accuracy: 0.9555
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: 8
- eval_batch_size: 8
- 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 | 71 | 0.1547 | 0.5048 | 0.3774 | 0.4319 | 0.9430 |
| No log | 2.0 | 142 | 0.1542 | 0.5965 | 0.4071 | 0.4839 | 0.9495 |
| No log | 3.0 | 213 | 0.1369 | 0.5519 | 0.5160 | 0.5334 | 0.9516 |
| No log | 4.0 | 284 | 0.1435 | 0.5622 | 0.4989 | 0.5287 | 0.9512 |
| No log | 5.0 | 355 | 0.1542 | 0.5920 | 0.5575 | 0.5742 | 0.9536 |
| No log | 6.0 | 426 | 0.1625 | 0.6069 | 0.5663 | 0.5859 | 0.9546 |
| No log | 7.0 | 497 | 0.1779 | 0.5936 | 0.5830 | 0.5883 | 0.9526 |
| 0.0978 | 8.0 | 568 | 0.1827 | 0.6035 | 0.5784 | 0.5907 | 0.9546 |
| 0.0978 | 9.0 | 639 | 0.2026 | 0.6121 | 0.5685 | 0.5895 | 0.9546 |
| 0.0978 | 10.0 | 710 | 0.2057 | 0.6288 | 0.5579 | 0.5912 | 0.9555 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
