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-classifier
  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-classifier

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: 0.8761
- Accuracy: 0.5812

## 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: 10

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Accuracy |
|:-------------:|:-----:|:------:|:---------------:|:--------:|
| 0.915         | 0.44  | 5000   | 0.9458          | 0.5413   |
| 0.9446        | 0.87  | 10000  | 0.9111          | 0.5734   |
| 0.9701        | 1.31  | 15000  | 0.9020          | 0.5728   |
| 1.0364        | 1.75  | 20000  | 0.9053          | 0.5746   |
| 1.0566        | 2.18  | 25000  | 0.8934          | 0.5723   |
| 0.7617        | 2.62  | 30000  | 0.8903          | 0.5697   |
| 0.8615        | 3.06  | 35000  | 0.8825          | 0.5886   |
| 0.8974        | 3.49  | 40000  | 0.8896          | 0.5760   |
| 0.877         | 3.93  | 45000  | 0.8854          | 0.5827   |
| 0.8099        | 4.37  | 50000  | 0.8864          | 0.5754   |
| 0.8527        | 4.8   | 55000  | 0.8825          | 0.5853   |
| 0.892         | 5.24  | 60000  | 0.8869          | 0.5714   |
| 1.0117        | 5.68  | 65000  | 0.8835          | 0.5780   |
| 0.8814        | 6.11  | 70000  | 0.8770          | 0.5812   |
| 1.0064        | 6.55  | 75000  | 0.8845          | 0.5771   |
| 0.9091        | 6.99  | 80000  | 0.8837          | 0.5740   |
| 0.8869        | 7.42  | 85000  | 0.8780          | 0.5839   |
| 0.9656        | 7.86  | 90000  | 0.8916          | 0.5668   |
| 0.8205        | 8.3   | 95000  | 0.8767          | 0.5855   |
| 0.9256        | 8.73  | 100000 | 0.8772          | 0.5840   |
| 0.8649        | 9.17  | 105000 | 0.8769          | 0.5824   |
| 0.9214        | 9.61  | 110000 | 0.8761          | 0.5812   |


### Framework versions

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