metadata
library_name: transformers
base_model: medicalai/ClinicalBERT
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ClinicalBERT-full-finetuned-ner-pablo
results: []
ClinicalBERT-full-finetuned-ner-pablo
This model is a fine-tuned version of medicalai/ClinicalBERT on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0815
- Precision: 0.7883
- Recall: 0.7691
- F1: 0.7786
- Accuracy: 0.9751
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 231 | 0.0931 | 0.7518 | 0.7606 | 0.7562 | 0.9719 |
| No log | 2.0 | 462 | 0.0815 | 0.7883 | 0.7691 | 0.7786 | 0.9751 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1