med_ner_2
This model is a fine-tuned version of prajjwal1/bert-tiny on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0295
- Overall Precision: 1.0
- Overall Recall: 0.9831
- Overall F1: 0.9915
- Overall Accuracy: 0.9977
- Age F1: 0.9888
- Yob F1: 1.0
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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 250
Training results
Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Age F1 | Yob F1 |
---|---|---|---|---|---|---|---|---|---|
0.0 | 47.62 | 1000 | 0.0364 | 1.0 | 0.9831 | 0.9915 | 0.9977 | 0.9888 | 1.0 |
0.0 | 95.24 | 2000 | 0.0363 | 1.0 | 0.9831 | 0.9915 | 0.9977 | 0.9888 | 1.0 |
0.0 | 142.86 | 3000 | 0.0279 | 1.0 | 0.9831 | 0.9915 | 0.9977 | 0.9888 | 1.0 |
0.0 | 190.48 | 4000 | 0.0265 | 1.0 | 0.9831 | 0.9915 | 0.9977 | 0.9888 | 1.0 |
0.0 | 238.1 | 5000 | 0.0295 | 1.0 | 0.9831 | 0.9915 | 0.9977 | 0.9888 | 1.0 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
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Base model
prajjwal1/bert-tiny