---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: model_handwritenNumbers-nesanchezo
  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. -->

# model_handwritenNumbers-nesanchezo

This model is a fine-tuned version of [farleyknight-org-username/vit-base-mnist](https://huggingface.co/farleyknight-org-username/vit-base-mnist) on the handwriten-Numbers dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0807
- Accuracy: 0.9839

## 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: 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.396         | 0.34  | 500  | 0.1925          | 0.9470   |
| 0.2672        | 0.67  | 1000 | 0.2655          | 0.9297   |
| 0.2261        | 1.01  | 1500 | 0.1767          | 0.9548   |
| 0.1603        | 1.34  | 2000 | 0.1423          | 0.9658   |
| 0.1308        | 1.68  | 2500 | 0.1378          | 0.9709   |
| 0.1187        | 2.02  | 3000 | 0.1168          | 0.9737   |
| 0.0873        | 2.35  | 3500 | 0.0857          | 0.9823   |
| 0.0686        | 2.69  | 4000 | 0.1188          | 0.9753   |
| 0.0635        | 3.03  | 4500 | 0.0836          | 0.9804   |
| 0.034         | 3.36  | 5000 | 0.0807          | 0.9839   |
| 0.0155        | 3.7   | 5500 | 0.0898          | 0.9823   |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.3