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_rms_00001_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: 0.870216306156406
---

<!-- 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_rms_00001_fold2

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: 0.8494
- Accuracy: 0.8702

## 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: 1e-05
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.391         | 1.0   | 75   | 0.3306          | 0.8569   |
| 0.2024        | 2.0   | 150  | 0.3078          | 0.8719   |
| 0.1659        | 3.0   | 225  | 0.3046          | 0.8636   |
| 0.1089        | 4.0   | 300  | 0.3233          | 0.8702   |
| 0.0832        | 5.0   | 375  | 0.4345          | 0.8552   |
| 0.0315        | 6.0   | 450  | 0.4227          | 0.8686   |
| 0.0247        | 7.0   | 525  | 0.5432          | 0.8652   |
| 0.0031        | 8.0   | 600  | 0.5857          | 0.8769   |
| 0.0058        | 9.0   | 675  | 0.5689          | 0.8619   |
| 0.0354        | 10.0  | 750  | 0.6368          | 0.8619   |
| 0.0193        | 11.0  | 825  | 0.5921          | 0.8752   |
| 0.0019        | 12.0  | 900  | 0.6514          | 0.8785   |
| 0.0447        | 13.0  | 975  | 0.6838          | 0.8686   |
| 0.0527        | 14.0  | 1050 | 0.6693          | 0.8735   |
| 0.0047        | 15.0  | 1125 | 0.6444          | 0.8735   |
| 0.0064        | 16.0  | 1200 | 0.7052          | 0.8719   |
| 0.0002        | 17.0  | 1275 | 0.7289          | 0.8636   |
| 0.0092        | 18.0  | 1350 | 0.7405          | 0.8669   |
| 0.0001        | 19.0  | 1425 | 0.7743          | 0.8619   |
| 0.0038        | 20.0  | 1500 | 0.7512          | 0.8686   |
| 0.0001        | 21.0  | 1575 | 0.8249          | 0.8602   |
| 0.0001        | 22.0  | 1650 | 0.7832          | 0.8686   |
| 0.0001        | 23.0  | 1725 | 0.8312          | 0.8636   |
| 0.0           | 24.0  | 1800 | 0.7877          | 0.8669   |
| 0.0           | 25.0  | 1875 | 0.7958          | 0.8719   |
| 0.0001        | 26.0  | 1950 | 0.7718          | 0.8752   |
| 0.0055        | 27.0  | 2025 | 0.7918          | 0.8686   |
| 0.0032        | 28.0  | 2100 | 0.8022          | 0.8735   |
| 0.0023        | 29.0  | 2175 | 0.8185          | 0.8735   |
| 0.0031        | 30.0  | 2250 | 0.8365          | 0.8735   |
| 0.0028        | 31.0  | 2325 | 0.7946          | 0.8686   |
| 0.0           | 32.0  | 2400 | 0.8222          | 0.8752   |
| 0.0           | 33.0  | 2475 | 0.7981          | 0.8719   |
| 0.0           | 34.0  | 2550 | 0.8313          | 0.8752   |
| 0.0084        | 35.0  | 2625 | 0.8895          | 0.8702   |
| 0.0           | 36.0  | 2700 | 0.8170          | 0.8686   |
| 0.0           | 37.0  | 2775 | 0.8344          | 0.8752   |
| 0.0           | 38.0  | 2850 | 0.8561          | 0.8735   |
| 0.0022        | 39.0  | 2925 | 0.8329          | 0.8702   |
| 0.0           | 40.0  | 3000 | 0.8473          | 0.8719   |
| 0.0026        | 41.0  | 3075 | 0.8354          | 0.8686   |
| 0.0           | 42.0  | 3150 | 0.8451          | 0.8735   |
| 0.0025        | 43.0  | 3225 | 0.8430          | 0.8735   |
| 0.0025        | 44.0  | 3300 | 0.8484          | 0.8719   |
| 0.0           | 45.0  | 3375 | 0.8461          | 0.8702   |
| 0.0           | 46.0  | 3450 | 0.8473          | 0.8735   |
| 0.0023        | 47.0  | 3525 | 0.8487          | 0.8719   |
| 0.0           | 48.0  | 3600 | 0.8492          | 0.8702   |
| 0.0022        | 49.0  | 3675 | 0.8491          | 0.8686   |
| 0.0022        | 50.0  | 3750 | 0.8494          | 0.8702   |


### Framework versions

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