bert-base-multilingual-cased_0319_J
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: 0.0355
- Precision: 0.9776
- Recall: 0.9791
- F1: 0.9784
- Accuracy: 0.9949
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: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 95 | 0.2410 | 0.6320 | 0.7491 | 0.6856 | 0.9475 |
| No log | 2.0 | 190 | 0.0483 | 0.9430 | 0.9522 | 0.9476 | 0.9912 |
| No log | 3.0 | 285 | 0.0379 | 0.9710 | 0.9746 | 0.9728 | 0.9938 |
| No log | 4.0 | 380 | 0.0382 | 0.9645 | 0.9731 | 0.9688 | 0.9940 |
| No log | 5.0 | 475 | 0.0357 | 0.9703 | 0.9761 | 0.9732 | 0.9941 |
| No log | 6.0 | 570 | 0.0367 | 0.9710 | 0.9761 | 0.9736 | 0.9943 |
| No log | 7.0 | 665 | 0.0376 | 0.9732 | 0.9761 | 0.9746 | 0.9943 |
| No log | 8.0 | 760 | 0.0355 | 0.9776 | 0.9791 | 0.9784 | 0.9949 |
| No log | 9.0 | 855 | 0.0364 | 0.9718 | 0.9768 | 0.9743 | 0.9946 |
| No log | 10.0 | 950 | 0.0361 | 0.9747 | 0.9776 | 0.9761 | 0.9947 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.0+cu117
- Datasets 2.8.0
- Tokenizers 0.12.1