bert-base-multilingual-uncased-finetuned-classification
This model is a fine-tuned version of google-bert/bert-base-multilingual-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1394
- Accuracy: 0.9524
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: 16
- 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 |
|---|---|---|---|---|
| No log | 1.0 | 20 | 0.1029 | 0.9810 |
| No log | 2.0 | 40 | 0.1137 | 0.9524 |
| No log | 3.0 | 60 | 0.1153 | 0.9524 |
| No log | 4.0 | 80 | 0.1170 | 0.9524 |
| No log | 5.0 | 100 | 0.1208 | 0.9524 |
| No log | 6.0 | 120 | 0.1064 | 0.9810 |
| No log | 7.0 | 140 | 0.1344 | 0.9524 |
| No log | 8.0 | 160 | 0.1237 | 0.9524 |
| No log | 9.0 | 180 | 0.1146 | 0.9524 |
| No log | 10.0 | 200 | 0.1330 | 0.9524 |
| No log | 11.0 | 220 | 0.1285 | 0.9524 |
| No log | 12.0 | 240 | 0.1291 | 0.9524 |
| No log | 13.0 | 260 | 0.1335 | 0.9524 |
| No log | 14.0 | 280 | 0.1380 | 0.9524 |
| No log | 15.0 | 300 | 0.1394 | 0.9524 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for yuridrcosta/bert-base-multilingual-uncased-finetuned-classification
Base model
google-bert/bert-base-multilingual-uncased