metadata
base_model: bert-base-uncased
library_name: transformers
license: apache-2.0
metrics:
- accuracy
- f1
tags:
- generated_from_trainer
model-index:
- name: Finetuning_Bert_ClinicalNotes_Diagnosis_Classification
results: []
Finetuning_Bert_ClinicalNotes_Diagnosis_Classification
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0028
- Accuracy: 1.0
- 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
---|---|---|---|---|---|
No log | 1.0 | 438 | 0.0226 | 1.0 | 1.0 |
0.6724 | 2.0 | 876 | 0.0069 | 1.0 | 1.0 |
0.0134 | 3.0 | 1314 | 0.0041 | 1.0 | 1.0 |
0.0062 | 4.0 | 1752 | 0.0031 | 1.0 | 1.0 |
0.0044 | 5.0 | 2190 | 0.0028 | 1.0 | 1.0 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1