---
license: mit
base_model: prajjwal1/bert-tiny
tags:
- generated_from_trainer
model-index:
- name: med_ner_2
  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. -->

# med_ner_2

This model is a fine-tuned version of [prajjwal1/bert-tiny](https://huggingface.co/prajjwal1/bert-tiny) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0295
- Overall Precision: 1.0
- Overall Recall: 0.9831
- Overall F1: 0.9915
- Overall Accuracy: 0.9977
- Age F1: 0.9888
- Yob 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 250

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Age F1 | Yob F1 |
|:-------------:|:------:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:------:|:------:|
| 0.0           | 47.62  | 1000 | 0.0364          | 1.0               | 0.9831         | 0.9915     | 0.9977           | 0.9888 | 1.0    |
| 0.0           | 95.24  | 2000 | 0.0363          | 1.0               | 0.9831         | 0.9915     | 0.9977           | 0.9888 | 1.0    |
| 0.0           | 142.86 | 3000 | 0.0279          | 1.0               | 0.9831         | 0.9915     | 0.9977           | 0.9888 | 1.0    |
| 0.0           | 190.48 | 4000 | 0.0265          | 1.0               | 0.9831         | 0.9915     | 0.9977           | 0.9888 | 1.0    |
| 0.0           | 238.1  | 5000 | 0.0295          | 1.0               | 0.9831         | 0.9915     | 0.9977           | 0.9888 | 1.0    |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1