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NLP-HIBA2_DisTEMIST_fine_tuned_DistilBERT-pretrained-model
This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2224
- Precision: 0.5553
- Recall: 0.5163
- F1: 0.5351
- Accuracy: 0.9502
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 | 0.1767 | 0.4612 | 0.4905 | 0.4754 | 0.9399 |
| No log | 2.0 | 142 | 0.1696 | 0.5173 | 0.4400 | 0.4755 | 0.9481 |
| No log | 3.0 | 213 | 0.1782 | 0.5189 | 0.5290 | 0.5239 | 0.9485 |
| No log | 4.0 | 284 | 0.1928 | 0.5275 | 0.4988 | 0.5128 | 0.9475 |
| No log | 5.0 | 355 | 0.2020 | 0.5800 | 0.4782 | 0.5242 | 0.9512 |
| No log | 6.0 | 426 | 0.2091 | 0.5645 | 0.4849 | 0.5217 | 0.9506 |
| No log | 7.0 | 497 | 0.2035 | 0.5608 | 0.5095 | 0.5339 | 0.9511 |
| 0.0531 | 8.0 | 568 | 0.2150 | 0.5282 | 0.5385 | 0.5333 | 0.9484 |
| 0.0531 | 9.0 | 639 | 0.2224 | 0.5639 | 0.5068 | 0.5338 | 0.9507 |
| 0.0531 | 10.0 | 710 | 0.2224 | 0.5553 | 0.5163 | 0.5351 | 0.9502 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
