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BERT_AA_IMDB_Top5_WithoutOOC_082023_MultilingualBertBase
This model is a fine-tuned version of bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0147
- Accuracy: 0.9971
- F1: 0.9971
- Precision: 0.9971
- Recall: 0.9971
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: 12
- eval_batch_size: 12
- 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 | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.158 | 1.0 | 613 | 0.0328 | 0.9918 | 0.9918 | 0.9921 | 0.9918 |
| 0.0184 | 2.0 | 1226 | 0.0466 | 0.9918 | 0.9918 | 0.9919 | 0.9918 |
| 0.0141 | 3.0 | 1839 | 0.0174 | 0.9967 | 0.9967 | 0.9967 | 0.9967 |
| 0.0045 | 4.0 | 2452 | 0.0121 | 0.9967 | 0.9967 | 0.9967 | 0.9967 |
| 0.0001 | 5.0 | 3065 | 0.0132 | 0.9975 | 0.9975 | 0.9976 | 0.9975 |
| 0.001 | 6.0 | 3678 | 0.0274 | 0.9959 | 0.9959 | 0.9959 | 0.9959 |
| 0.0001 | 7.0 | 4291 | 0.0282 | 0.9959 | 0.9959 | 0.9959 | 0.9959 |
| 0.0001 | 8.0 | 4904 | 0.0128 | 0.9980 | 0.9980 | 0.9980 | 0.9980 |
| 0.0001 | 9.0 | 5517 | 0.0188 | 0.9967 | 0.9967 | 0.9967 | 0.9967 |
| 0.0005 | 10.0 | 6130 | 0.0147 | 0.9971 | 0.9971 | 0.9971 | 0.9971 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.8.0
- Datasets 2.10.1
- Tokenizers 0.13.2
