metadata
license: mit
base_model: Clinical-AI-Apollo/Medical-NER
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: Medical-NER-finetuned-ner
results: []
Medical-NER-finetuned-ner
This model is a fine-tuned version of Clinical-AI-Apollo/Medical-NER on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0603
- Precision: 0.8160
- Recall: 0.8837
- F1: 0.8485
- Accuracy: 0.9837
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 | 340 | 0.0609 | 0.8136 | 0.8503 | 0.8316 | 0.9825 |
| 0.1068 | 2.0 | 680 | 0.0520 | 0.8096 | 0.8819 | 0.8442 | 0.9835 |
| 0.0335 | 3.0 | 1020 | 0.0603 | 0.8160 | 0.8837 | 0.8485 | 0.9837 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2