model_all
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: 1.4240
- Accuracy: 0.7937
- F1: 0.7937
- Precision: 0.7937
- Recall: 0.7937
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: 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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 1.9958 | 1.0 | 753 | 1.0623 | 0.6951 | 0.6951 | 0.6951 | 0.6951 |
| 0.3471 | 2.0 | 1506 | 1.0435 | 0.7579 | 0.7579 | 0.7579 | 0.7579 |
| 0.1329 | 3.0 | 2259 | 1.1884 | 0.7844 | 0.7844 | 0.7844 | 0.7844 |
| 0.0612 | 4.0 | 3012 | 1.3113 | 0.7851 | 0.7851 | 0.7851 | 0.7851 |
| 0.0263 | 5.0 | 3765 | 1.4240 | 0.7937 | 0.7937 | 0.7937 | 0.7937 |
| 0.0237 | 6.0 | 4518 | 1.5578 | 0.7824 | 0.7824 | 0.7824 | 0.7824 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0
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Base model
google-bert/bert-base-multilingual-cased