fine_tuned_mBERT
This model is a fine-tuned version of google-bert/bert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1614
- F1: 0.7869
- F5: 0.8020
- Precision: 0.75
- Recall: 0.8276
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | F5 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 30 | 0.2615 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 2.0 | 60 | 0.1838 | 0.5333 | 0.4626 | 0.8889 | 0.3810 |
| No log | 3.0 | 90 | 0.2338 | 0.3077 | 0.2491 | 0.8 | 0.1905 |
| No log | 4.0 | 120 | 0.2003 | 0.6667 | 0.6268 | 0.8 | 0.5714 |
| No log | 5.0 | 150 | 0.2643 | 0.5 | 0.4906 | 0.5263 | 0.4762 |
| No log | 6.0 | 180 | 0.2211 | 0.6486 | 0.6168 | 0.75 | 0.5714 |
| No log | 7.0 | 210 | 0.2233 | 0.6 | 0.6391 | 0.5172 | 0.7143 |
| No log | 8.0 | 240 | 0.3328 | 0.5 | 0.5647 | 0.3846 | 0.7143 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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Base model
google-bert/bert-base-multilingual-cased