---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_deit_small_sgd_0001_fold5
  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: 0.4634146341463415
---

<!-- 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. -->

# hushem_40x_deit_small_sgd_0001_fold5

This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1092
- Accuracy: 0.4634

## 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: 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.7467        | 1.0   | 220   | 1.6098          | 0.2683   |
| 1.5306        | 2.0   | 440   | 1.5314          | 0.2683   |
| 1.3989        | 3.0   | 660   | 1.5004          | 0.2439   |
| 1.3588        | 4.0   | 880   | 1.4811          | 0.2195   |
| 1.3953        | 5.0   | 1100  | 1.4639          | 0.2683   |
| 1.3096        | 6.0   | 1320  | 1.4476          | 0.2439   |
| 1.2743        | 7.0   | 1540  | 1.4329          | 0.2683   |
| 1.2405        | 8.0   | 1760  | 1.4190          | 0.2927   |
| 1.253         | 9.0   | 1980  | 1.4052          | 0.3171   |
| 1.2253        | 10.0  | 2200  | 1.3912          | 0.3171   |
| 1.1663        | 11.0  | 2420  | 1.3767          | 0.3659   |
| 1.1699        | 12.0  | 2640  | 1.3616          | 0.3659   |
| 1.1615        | 13.0  | 2860  | 1.3463          | 0.3659   |
| 1.0999        | 14.0  | 3080  | 1.3303          | 0.3902   |
| 1.1286        | 15.0  | 3300  | 1.3148          | 0.3659   |
| 1.1333        | 16.0  | 3520  | 1.2990          | 0.3659   |
| 1.075         | 17.0  | 3740  | 1.2842          | 0.3659   |
| 1.0779        | 18.0  | 3960  | 1.2709          | 0.3659   |
| 1.0652        | 19.0  | 4180  | 1.2579          | 0.3659   |
| 1.0475        | 20.0  | 4400  | 1.2462          | 0.3659   |
| 1.0095        | 21.0  | 4620  | 1.2350          | 0.3902   |
| 1.0607        | 22.0  | 4840  | 1.2247          | 0.3902   |
| 1.0243        | 23.0  | 5060  | 1.2151          | 0.4146   |
| 1.0174        | 24.0  | 5280  | 1.2064          | 0.4146   |
| 0.9654        | 25.0  | 5500  | 1.1977          | 0.3902   |
| 1.017         | 26.0  | 5720  | 1.1899          | 0.4146   |
| 1.0002        | 27.0  | 5940  | 1.1820          | 0.3902   |
| 1.0191        | 28.0  | 6160  | 1.1750          | 0.3902   |
| 0.9876        | 29.0  | 6380  | 1.1683          | 0.3902   |
| 0.9526        | 30.0  | 6600  | 1.1623          | 0.4146   |
| 0.9957        | 31.0  | 6820  | 1.1566          | 0.4390   |
| 0.9778        | 32.0  | 7040  | 1.1513          | 0.4390   |
| 0.9223        | 33.0  | 7260  | 1.1464          | 0.4634   |
| 0.9281        | 34.0  | 7480  | 1.1418          | 0.4634   |
| 0.9107        | 35.0  | 7700  | 1.1376          | 0.4634   |
| 0.9485        | 36.0  | 7920  | 1.1336          | 0.4634   |
| 0.9035        | 37.0  | 8140  | 1.1298          | 0.4634   |
| 0.9223        | 38.0  | 8360  | 1.1266          | 0.4634   |
| 0.9312        | 39.0  | 8580  | 1.1235          | 0.4634   |
| 0.8782        | 40.0  | 8800  | 1.1209          | 0.4634   |
| 0.9252        | 41.0  | 9020  | 1.1184          | 0.4634   |
| 0.8989        | 42.0  | 9240  | 1.1164          | 0.4634   |
| 0.8959        | 43.0  | 9460  | 1.1145          | 0.4634   |
| 0.8589        | 44.0  | 9680  | 1.1130          | 0.4634   |
| 0.8899        | 45.0  | 9900  | 1.1117          | 0.4634   |
| 0.8915        | 46.0  | 10120 | 1.1107          | 0.4634   |
| 0.9043        | 47.0  | 10340 | 1.1100          | 0.4634   |
| 0.8309        | 48.0  | 10560 | 1.1095          | 0.4634   |
| 0.8724        | 49.0  | 10780 | 1.1093          | 0.4634   |
| 0.9011        | 50.0  | 11000 | 1.1092          | 0.4634   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2