---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_5x_deit_tiny_adamax_00001_fold2
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: test
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8801996672212978
---

<!-- 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. -->

# smids_5x_deit_tiny_adamax_00001_fold2

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9976
- Accuracy: 0.8802

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.452         | 1.0   | 375   | 0.3866          | 0.8403   |
| 0.2847        | 2.0   | 750   | 0.3266          | 0.8602   |
| 0.2241        | 3.0   | 1125  | 0.3108          | 0.8602   |
| 0.1563        | 4.0   | 1500  | 0.3106          | 0.8785   |
| 0.1317        | 5.0   | 1875  | 0.3206          | 0.8802   |
| 0.0972        | 6.0   | 2250  | 0.3257          | 0.8835   |
| 0.0878        | 7.0   | 2625  | 0.3684          | 0.8752   |
| 0.0825        | 8.0   | 3000  | 0.3750          | 0.8819   |
| 0.0645        | 9.0   | 3375  | 0.4082          | 0.8852   |
| 0.0305        | 10.0  | 3750  | 0.4870          | 0.8769   |
| 0.0215        | 11.0  | 4125  | 0.4928          | 0.8869   |
| 0.037         | 12.0  | 4500  | 0.5391          | 0.8802   |
| 0.0369        | 13.0  | 4875  | 0.6212          | 0.8719   |
| 0.0169        | 14.0  | 5250  | 0.6496          | 0.8819   |
| 0.0205        | 15.0  | 5625  | 0.7009          | 0.8769   |
| 0.0006        | 16.0  | 6000  | 0.7474          | 0.8735   |
| 0.0156        | 17.0  | 6375  | 0.7683          | 0.8735   |
| 0.0004        | 18.0  | 6750  | 0.7918          | 0.8752   |
| 0.0002        | 19.0  | 7125  | 0.8032          | 0.8819   |
| 0.0009        | 20.0  | 7500  | 0.8199          | 0.8835   |
| 0.0001        | 21.0  | 7875  | 0.8709          | 0.8835   |
| 0.0001        | 22.0  | 8250  | 0.8571          | 0.8785   |
| 0.0001        | 23.0  | 8625  | 0.8684          | 0.8785   |
| 0.0001        | 24.0  | 9000  | 0.8915          | 0.8785   |
| 0.0           | 25.0  | 9375  | 0.9054          | 0.8785   |
| 0.0001        | 26.0  | 9750  | 0.9181          | 0.8802   |
| 0.0           | 27.0  | 10125 | 0.9162          | 0.8785   |
| 0.0           | 28.0  | 10500 | 0.9185          | 0.8802   |
| 0.0           | 29.0  | 10875 | 0.9373          | 0.8769   |
| 0.0           | 30.0  | 11250 | 0.9455          | 0.8819   |
| 0.0093        | 31.0  | 11625 | 0.9243          | 0.8785   |
| 0.025         | 32.0  | 12000 | 0.9658          | 0.8769   |
| 0.0144        | 33.0  | 12375 | 0.9598          | 0.8785   |
| 0.0           | 34.0  | 12750 | 0.9760          | 0.8802   |
| 0.0           | 35.0  | 13125 | 0.9707          | 0.8852   |
| 0.0           | 36.0  | 13500 | 0.9857          | 0.8785   |
| 0.0           | 37.0  | 13875 | 0.9774          | 0.8819   |
| 0.0           | 38.0  | 14250 | 0.9769          | 0.8785   |
| 0.0           | 39.0  | 14625 | 0.9854          | 0.8835   |
| 0.0009        | 40.0  | 15000 | 0.9942          | 0.8769   |
| 0.0           | 41.0  | 15375 | 0.9901          | 0.8802   |
| 0.0117        | 42.0  | 15750 | 0.9844          | 0.8785   |
| 0.0061        | 43.0  | 16125 | 0.9978          | 0.8785   |
| 0.0061        | 44.0  | 16500 | 1.0013          | 0.8802   |
| 0.0108        | 45.0  | 16875 | 1.0012          | 0.8769   |
| 0.0           | 46.0  | 17250 | 0.9950          | 0.8785   |
| 0.0106        | 47.0  | 17625 | 0.9952          | 0.8785   |
| 0.0           | 48.0  | 18000 | 0.9951          | 0.8785   |
| 0.0097        | 49.0  | 18375 | 0.9966          | 0.8785   |
| 0.0033        | 50.0  | 18750 | 0.9976          | 0.8802   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.1+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2