transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-small-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
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_0001_fold1
  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: 0.6193656093489148
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# smids_1x_deit_small_sgd_0001_fold1

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: 0.9238
- Accuracy: 0.6194

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1708        | 1.0   | 76   | 1.1671          | 0.2154   |
| 1.1329        | 2.0   | 152  | 1.1541          | 0.2421   |
| 1.1491        | 3.0   | 228  | 1.1427          | 0.2538   |
| 1.1383        | 4.0   | 304  | 1.1321          | 0.2654   |
| 1.095         | 5.0   | 380  | 1.1227          | 0.2838   |
| 1.1047        | 6.0   | 456  | 1.1138          | 0.3055   |
| 1.1073        | 7.0   | 532  | 1.1055          | 0.3322   |
| 1.1015        | 8.0   | 608  | 1.0974          | 0.3456   |
| 1.0955        | 9.0   | 684  | 1.0899          | 0.3639   |
| 1.0349        | 10.0  | 760  | 1.0825          | 0.3706   |
| 1.0617        | 11.0  | 836  | 1.0752          | 0.3957   |
| 1.0611        | 12.0  | 912  | 1.0681          | 0.4140   |
| 1.0517        | 13.0  | 988  | 1.0610          | 0.4240   |
| 1.0458        | 14.0  | 1064 | 1.0541          | 0.4357   |
| 1.0495        | 15.0  | 1140 | 1.0471          | 0.4391   |
| 1.032         | 16.0  | 1216 | 1.0402          | 0.4457   |
| 1.0199        | 17.0  | 1292 | 1.0334          | 0.4608   |
| 1.0216        | 18.0  | 1368 | 1.0267          | 0.4691   |
| 1.0137        | 19.0  | 1444 | 1.0202          | 0.4825   |
| 1.0117        | 20.0  | 1520 | 1.0136          | 0.5058   |
| 0.9951        | 21.0  | 1596 | 1.0073          | 0.5142   |
| 0.9978        | 22.0  | 1672 | 1.0011          | 0.5175   |
| 0.9715        | 23.0  | 1748 | 0.9952          | 0.5242   |
| 0.9775        | 24.0  | 1824 | 0.9895          | 0.5392   |
| 0.9696        | 25.0  | 1900 | 0.9841          | 0.5409   |
| 0.9601        | 26.0  | 1976 | 0.9789          | 0.5492   |
| 0.9807        | 27.0  | 2052 | 0.9740          | 0.5593   |
| 0.9357        | 28.0  | 2128 | 0.9694          | 0.5626   |
| 0.9396        | 29.0  | 2204 | 0.9650          | 0.5710   |
| 0.9629        | 30.0  | 2280 | 0.9608          | 0.5743   |
| 0.9473        | 31.0  | 2356 | 0.9570          | 0.5826   |
| 0.9153        | 32.0  | 2432 | 0.9532          | 0.5860   |
| 0.9343        | 33.0  | 2508 | 0.9497          | 0.5927   |
| 0.953         | 34.0  | 2584 | 0.9465          | 0.5993   |
| 0.949         | 35.0  | 2660 | 0.9435          | 0.6027   |
| 0.9108        | 36.0  | 2736 | 0.9407          | 0.6043   |
| 0.9432        | 37.0  | 2812 | 0.9382          | 0.6060   |
| 0.9019        | 38.0  | 2888 | 0.9358          | 0.6093   |
| 0.9269        | 39.0  | 2964 | 0.9337          | 0.6093   |
| 0.9369        | 40.0  | 3040 | 0.9318          | 0.6110   |
| 0.8967        | 41.0  | 3116 | 0.9301          | 0.6110   |
| 0.9379        | 42.0  | 3192 | 0.9286          | 0.6144   |
| 0.8809        | 43.0  | 3268 | 0.9273          | 0.6160   |
| 0.9188        | 44.0  | 3344 | 0.9263          | 0.6177   |
| 0.8925        | 45.0  | 3420 | 0.9254          | 0.6177   |
| 0.8985        | 46.0  | 3496 | 0.9247          | 0.6177   |
| 0.9127        | 47.0  | 3572 | 0.9242          | 0.6194   |
| 0.9099        | 48.0  | 3648 | 0.9239          | 0.6194   |
| 0.9072        | 49.0  | 3724 | 0.9238          | 0.6194   |
| 0.9001        | 50.0  | 3800 | 0.9238          | 0.6194   |


### Framework versions

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