---
license: apache-2.0
base_model: facebook/deit-small-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_1x_deit_small_sgd_001_fold3
  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: 0.8716666666666667
---

<!-- 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_small_sgd_001_fold3

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: 0.3620
- Accuracy: 0.8717

## 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: 0.001
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9897        | 1.0   | 75   | 0.9617          | 0.5517   |
| 0.8723        | 2.0   | 150  | 0.8626          | 0.625    |
| 0.7649        | 3.0   | 225  | 0.7773          | 0.7033   |
| 0.6947        | 4.0   | 300  | 0.7095          | 0.7417   |
| 0.6117        | 5.0   | 375  | 0.6569          | 0.7517   |
| 0.5694        | 6.0   | 450  | 0.6132          | 0.7833   |
| 0.5545        | 7.0   | 525  | 0.5789          | 0.79     |
| 0.4978        | 8.0   | 600  | 0.5508          | 0.7967   |
| 0.5086        | 9.0   | 675  | 0.5269          | 0.8017   |
| 0.4854        | 10.0  | 750  | 0.5107          | 0.8033   |
| 0.442         | 11.0  | 825  | 0.4925          | 0.815    |
| 0.4253        | 12.0  | 900  | 0.4789          | 0.8217   |
| 0.4589        | 13.0  | 975  | 0.4669          | 0.8217   |
| 0.402         | 14.0  | 1050 | 0.4553          | 0.82     |
| 0.3349        | 15.0  | 1125 | 0.4468          | 0.8283   |
| 0.3869        | 16.0  | 1200 | 0.4398          | 0.8333   |
| 0.3789        | 17.0  | 1275 | 0.4312          | 0.8367   |
| 0.3564        | 18.0  | 1350 | 0.4255          | 0.84     |
| 0.3321        | 19.0  | 1425 | 0.4198          | 0.84     |
| 0.3788        | 20.0  | 1500 | 0.4135          | 0.8383   |
| 0.3599        | 21.0  | 1575 | 0.4108          | 0.8417   |
| 0.3259        | 22.0  | 1650 | 0.4045          | 0.8417   |
| 0.3384        | 23.0  | 1725 | 0.4010          | 0.8433   |
| 0.3143        | 24.0  | 1800 | 0.3966          | 0.8433   |
| 0.3495        | 25.0  | 1875 | 0.3938          | 0.8483   |
| 0.3642        | 26.0  | 1950 | 0.3902          | 0.8517   |
| 0.2826        | 27.0  | 2025 | 0.3879          | 0.855    |
| 0.3052        | 28.0  | 2100 | 0.3848          | 0.8533   |
| 0.3344        | 29.0  | 2175 | 0.3828          | 0.855    |
| 0.3229        | 30.0  | 2250 | 0.3809          | 0.8533   |
| 0.3173        | 31.0  | 2325 | 0.3785          | 0.8567   |
| 0.3012        | 32.0  | 2400 | 0.3761          | 0.8567   |
| 0.2954        | 33.0  | 2475 | 0.3749          | 0.8617   |
| 0.2924        | 34.0  | 2550 | 0.3731          | 0.8633   |
| 0.3077        | 35.0  | 2625 | 0.3719          | 0.8667   |
| 0.3047        | 36.0  | 2700 | 0.3705          | 0.8667   |
| 0.2425        | 37.0  | 2775 | 0.3691          | 0.8683   |
| 0.3384        | 38.0  | 2850 | 0.3680          | 0.8683   |
| 0.2795        | 39.0  | 2925 | 0.3666          | 0.8683   |
| 0.2754        | 40.0  | 3000 | 0.3660          | 0.87     |
| 0.2793        | 41.0  | 3075 | 0.3650          | 0.8683   |
| 0.288         | 42.0  | 3150 | 0.3645          | 0.87     |
| 0.3153        | 43.0  | 3225 | 0.3639          | 0.87     |
| 0.2599        | 44.0  | 3300 | 0.3636          | 0.8717   |
| 0.3229        | 45.0  | 3375 | 0.3630          | 0.8717   |
| 0.297         | 46.0  | 3450 | 0.3626          | 0.8717   |
| 0.2632        | 47.0  | 3525 | 0.3624          | 0.8717   |
| 0.3026        | 48.0  | 3600 | 0.3623          | 0.8717   |
| 0.3009        | 49.0  | 3675 | 0.3621          | 0.8717   |
| 0.2576        | 50.0  | 3750 | 0.3620          | 0.8717   |


### Framework versions

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