---
license: apache-2.0
base_model: facebook/deit-tiny-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_1x_deit_tiny_sgd_0001_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: 0.6023294509151415
---

<!-- 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_1x_deit_tiny_sgd_0001_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: 0.8723
- Accuracy: 0.6023

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2913        | 1.0   | 75   | 1.2725          | 0.3394   |
| 1.2246        | 2.0   | 150  | 1.2089          | 0.3444   |
| 1.1634        | 3.0   | 225  | 1.1639          | 0.3561   |
| 1.1405        | 4.0   | 300  | 1.1319          | 0.3661   |
| 1.1027        | 5.0   | 375  | 1.1096          | 0.3727   |
| 1.1314        | 6.0   | 450  | 1.0924          | 0.3960   |
| 1.1132        | 7.0   | 525  | 1.0784          | 0.4193   |
| 1.0729        | 8.0   | 600  | 1.0662          | 0.4359   |
| 1.064         | 9.0   | 675  | 1.0549          | 0.4526   |
| 1.0806        | 10.0  | 750  | 1.0450          | 0.4576   |
| 1.063         | 11.0  | 825  | 1.0356          | 0.4692   |
| 1.0489        | 12.0  | 900  | 1.0265          | 0.4792   |
| 1.0267        | 13.0  | 975  | 1.0180          | 0.4942   |
| 0.9878        | 14.0  | 1050 | 1.0096          | 0.5042   |
| 1.01          | 15.0  | 1125 | 1.0018          | 0.5058   |
| 0.9915        | 16.0  | 1200 | 0.9940          | 0.5092   |
| 0.9952        | 17.0  | 1275 | 0.9865          | 0.5158   |
| 1.0114        | 18.0  | 1350 | 0.9793          | 0.5258   |
| 1.0011        | 19.0  | 1425 | 0.9723          | 0.5308   |
| 0.9762        | 20.0  | 1500 | 0.9654          | 0.5358   |
| 1.0144        | 21.0  | 1575 | 0.9587          | 0.5408   |
| 0.9349        | 22.0  | 1650 | 0.9525          | 0.5507   |
| 0.9869        | 23.0  | 1725 | 0.9462          | 0.5557   |
| 0.9417        | 24.0  | 1800 | 0.9404          | 0.5591   |
| 0.9277        | 25.0  | 1875 | 0.9347          | 0.5591   |
| 0.9227        | 26.0  | 1950 | 0.9293          | 0.5707   |
| 0.9725        | 27.0  | 2025 | 0.9242          | 0.5674   |
| 0.9104        | 28.0  | 2100 | 0.9193          | 0.5691   |
| 0.9618        | 29.0  | 2175 | 0.9147          | 0.5774   |
| 0.8904        | 30.0  | 2250 | 0.9103          | 0.5824   |
| 0.9175        | 31.0  | 2325 | 0.9062          | 0.5840   |
| 0.916         | 32.0  | 2400 | 0.9024          | 0.5857   |
| 0.8843        | 33.0  | 2475 | 0.8990          | 0.5874   |
| 0.9346        | 34.0  | 2550 | 0.8956          | 0.5923   |
| 0.8711        | 35.0  | 2625 | 0.8924          | 0.5957   |
| 0.8808        | 36.0  | 2700 | 0.8897          | 0.5973   |
| 0.9043        | 37.0  | 2775 | 0.8870          | 0.5990   |
| 0.9738        | 38.0  | 2850 | 0.8847          | 0.5957   |
| 0.8643        | 39.0  | 2925 | 0.8826          | 0.5940   |
| 0.8918        | 40.0  | 3000 | 0.8806          | 0.5957   |
| 0.9135        | 41.0  | 3075 | 0.8789          | 0.5973   |
| 0.9187        | 42.0  | 3150 | 0.8773          | 0.5973   |
| 0.8721        | 43.0  | 3225 | 0.8760          | 0.5973   |
| 0.9047        | 44.0  | 3300 | 0.8749          | 0.5990   |
| 0.8511        | 45.0  | 3375 | 0.8740          | 0.6007   |
| 0.8649        | 46.0  | 3450 | 0.8732          | 0.6007   |
| 0.8917        | 47.0  | 3525 | 0.8727          | 0.6023   |
| 0.8901        | 48.0  | 3600 | 0.8724          | 0.6023   |
| 0.883         | 49.0  | 3675 | 0.8723          | 0.6023   |
| 0.8823        | 50.0  | 3750 | 0.8723          | 0.6023   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0