---
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_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: 0.855
---

<!-- 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_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: 0.3554
- Accuracy: 0.855

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9725        | 1.0   | 75   | 0.9578          | 0.58     |
| 0.8549        | 2.0   | 150  | 0.8545          | 0.6367   |
| 0.7685        | 3.0   | 225  | 0.7653          | 0.6967   |
| 0.7189        | 4.0   | 300  | 0.6967          | 0.7383   |
| 0.6469        | 5.0   | 375  | 0.6428          | 0.7567   |
| 0.5993        | 6.0   | 450  | 0.5995          | 0.7667   |
| 0.5809        | 7.0   | 525  | 0.5645          | 0.7717   |
| 0.5382        | 8.0   | 600  | 0.5378          | 0.7817   |
| 0.5132        | 9.0   | 675  | 0.5146          | 0.7933   |
| 0.5002        | 10.0  | 750  | 0.4976          | 0.7817   |
| 0.5258        | 11.0  | 825  | 0.4771          | 0.8033   |
| 0.4262        | 12.0  | 900  | 0.4625          | 0.8183   |
| 0.4371        | 13.0  | 975  | 0.4503          | 0.8217   |
| 0.4112        | 14.0  | 1050 | 0.4406          | 0.8217   |
| 0.3773        | 15.0  | 1125 | 0.4328          | 0.8183   |
| 0.3566        | 16.0  | 1200 | 0.4255          | 0.82     |
| 0.3898        | 17.0  | 1275 | 0.4160          | 0.83     |
| 0.3699        | 18.0  | 1350 | 0.4107          | 0.8233   |
| 0.3811        | 19.0  | 1425 | 0.4043          | 0.84     |
| 0.3869        | 20.0  | 1500 | 0.4001          | 0.8317   |
| 0.363         | 21.0  | 1575 | 0.3965          | 0.8383   |
| 0.3336        | 22.0  | 1650 | 0.3912          | 0.8433   |
| 0.334         | 23.0  | 1725 | 0.3876          | 0.8433   |
| 0.3158        | 24.0  | 1800 | 0.3862          | 0.845    |
| 0.309         | 25.0  | 1875 | 0.3831          | 0.8433   |
| 0.3223        | 26.0  | 1950 | 0.3821          | 0.84     |
| 0.3225        | 27.0  | 2025 | 0.3783          | 0.8417   |
| 0.3412        | 28.0  | 2100 | 0.3753          | 0.845    |
| 0.3183        | 29.0  | 2175 | 0.3735          | 0.8433   |
| 0.3062        | 30.0  | 2250 | 0.3707          | 0.8417   |
| 0.2914        | 31.0  | 2325 | 0.3702          | 0.8417   |
| 0.2994        | 32.0  | 2400 | 0.3684          | 0.84     |
| 0.3197        | 33.0  | 2475 | 0.3663          | 0.8467   |
| 0.2992        | 34.0  | 2550 | 0.3643          | 0.85     |
| 0.3245        | 35.0  | 2625 | 0.3629          | 0.8517   |
| 0.2966        | 36.0  | 2700 | 0.3625          | 0.8483   |
| 0.2581        | 37.0  | 2775 | 0.3619          | 0.8467   |
| 0.3008        | 38.0  | 2850 | 0.3609          | 0.8483   |
| 0.2884        | 39.0  | 2925 | 0.3604          | 0.85     |
| 0.3019        | 40.0  | 3000 | 0.3593          | 0.85     |
| 0.3288        | 41.0  | 3075 | 0.3590          | 0.8517   |
| 0.3129        | 42.0  | 3150 | 0.3580          | 0.855    |
| 0.2899        | 43.0  | 3225 | 0.3573          | 0.855    |
| 0.2709        | 44.0  | 3300 | 0.3568          | 0.855    |
| 0.2859        | 45.0  | 3375 | 0.3565          | 0.8533   |
| 0.3026        | 46.0  | 3450 | 0.3561          | 0.8533   |
| 0.2643        | 47.0  | 3525 | 0.3557          | 0.855    |
| 0.2626        | 48.0  | 3600 | 0.3556          | 0.855    |
| 0.2672        | 49.0  | 3675 | 0.3555          | 0.855    |
| 0.2682        | 50.0  | 3750 | 0.3554          | 0.855    |


### Framework versions

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