bert-base-dutch-cased-finetuned-mBERT-finetuned-ner
This model is a fine-tuned version of Matthijsvanhof/bert-base-dutch-cased-finetuned-mBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0127
- Precision: 0.9780
- Recall: 0.9889
- F1: 0.9834
- Accuracy: 0.9969
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 | 25 | 0.0395 | 0.8673 | 0.9444 | 0.9043 | 0.9876 |
No log | 2.0 | 50 | 0.0159 | 0.9780 | 0.9889 | 0.9834 | 0.9953 |
No log | 3.0 | 75 | 0.0127 | 0.9780 | 0.9889 | 0.9834 | 0.9969 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2+cpu
- Datasets 2.19.2
- Tokenizers 0.19.1
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