Improved-bert-multilingual
This model is a fine-tuned version of bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0118
- Accuracy: 0.78
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6856 | 0.55 | 50 | 0.6607 | 0.61 |
0.5729 | 1.1 | 100 | 0.5453 | 0.73 |
0.4649 | 1.65 | 150 | 0.5915 | 0.66 |
0.385 | 2.2 | 200 | 0.5824 | 0.7 |
0.343 | 2.75 | 250 | 0.4548 | 0.79 |
0.305 | 3.3 | 300 | 0.6585 | 0.71 |
0.2355 | 3.85 | 350 | 0.6034 | 0.77 |
0.2176 | 4.4 | 400 | 0.5191 | 0.79 |
0.2137 | 4.95 | 450 | 0.6655 | 0.73 |
0.181 | 5.49 | 500 | 0.6929 | 0.78 |
0.171 | 6.04 | 550 | 1.0172 | 0.65 |
0.1267 | 6.59 | 600 | 0.9904 | 0.67 |
0.1152 | 7.14 | 650 | 1.0817 | 0.65 |
0.1045 | 7.69 | 700 | 1.1231 | 0.66 |
0.0973 | 8.24 | 750 | 1.0118 | 0.78 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1
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Model tree for Anwaarma/Improved-bert-multilingual
Base model
google-bert/bert-base-multilingual-cased