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my_awesome_wnut_model
This model is a fine-tuned version of dbmdz/bert-base-turkish-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2661
- Precision: 0.8999
- Recall: 0.8933
- F1: 0.8966
- Accuracy: 0.9264
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: 3
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
No log | 1.0 | 488 | 0.3614 | 0.8731 | 0.8606 | 0.8668 | 0.9043 |
0.6843 | 2.0 | 976 | 0.2872 | 0.8927 | 0.8856 | 0.8891 | 0.9209 |
0.3517 | 3.0 | 1464 | 0.2661 | 0.8999 | 0.8933 | 0.8966 | 0.9264 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2