safetensors generated_from_trainer base_model:bert-base-cased license:apache-2.0 region:us
---
license: apache-2.0
base_model: bert-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: medical-diagnosis-classification-model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# medical-diagnosis-classification-model

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8962
- Accuracy: 0.5784

## 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.9083        | 0.44  | 5000  | 0.9480          | 0.5413   |
| 0.9345        | 0.87  | 10000 | 0.9236          | 0.5690   |
| 0.9558        | 1.31  | 15000 | 0.9112          | 0.5633   |
| 1.0294        | 1.75  | 20000 | 0.9150          | 0.5629   |
| 1.0029        | 2.18  | 25000 | 0.9197          | 0.5547   |
| 0.8028        | 2.62  | 30000 | 0.9018          | 0.5689   |
| 0.8739        | 3.06  | 35000 | 0.8926          | 0.5844   |
| 0.9352        | 3.49  | 40000 | 0.8988          | 0.5753   |
| 0.9041        | 3.93  | 45000 | 0.9014          | 0.5731   |
| 0.8445        | 4.37  | 50000 | 0.8990          | 0.5744   |
| 0.8374        | 4.8   | 55000 | 0.8962          | 0.5784   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
