---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert-medical-ner
  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. -->

# bert-medical-ner

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3752
- Precision: 0.7403
- Recall: 0.6800
- F1: 0.7089
- Accuracy: 0.9401

## 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: 64
- eval_batch_size: 64
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 63   | 0.3364          | 0.6802    | 0.6433 | 0.6612 | 0.9325   |
| No log        | 2.0   | 126  | 0.3434          | 0.6759    | 0.6789 | 0.6774 | 0.9331   |
| No log        | 3.0   | 189  | 0.3381          | 0.7297    | 0.6851 | 0.7067 | 0.9389   |
| No log        | 4.0   | 252  | 0.3470          | 0.6788    | 0.6942 | 0.6864 | 0.9333   |
| No log        | 5.0   | 315  | 0.3668          | 0.7392    | 0.6761 | 0.7062 | 0.9380   |
| No log        | 6.0   | 378  | 0.3722          | 0.7565    | 0.6710 | 0.7112 | 0.9416   |
| No log        | 7.0   | 441  | 0.3669          | 0.7253    | 0.6806 | 0.7022 | 0.9386   |
| 0.0633        | 8.0   | 504  | 0.3673          | 0.7250    | 0.6914 | 0.7078 | 0.9404   |
| 0.0633        | 9.0   | 567  | 0.3789          | 0.7456    | 0.6744 | 0.7082 | 0.9405   |
| 0.0633        | 10.0  | 630  | 0.3752          | 0.7403    | 0.6800 | 0.7089 | 0.9401   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3