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

# fine_tune_bert_output

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: 0.0094
- Overall Precision: 0.9722
- Overall Recall: 0.9722
- Overall F1: 0.9722
- Overall Accuracy: 0.9963
- Number Of Employees F1: 0.9722

## 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: 0.0002
- 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: 150

### Training results

| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Number Of Employees F1 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:----------------------:|
| 0.0011        | 50.0  | 1000 | 0.0046          | 0.9722            | 0.9722         | 0.9722     | 0.9963           | 0.9722                 |
| 0.0003        | 100.0 | 2000 | 0.0004          | 1.0               | 1.0            | 1.0        | 1.0              | 1.0                    |
| 0.0002        | 150.0 | 3000 | 0.0094          | 0.9722            | 0.9722         | 0.9722     | 0.9963           | 0.9722                 |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3