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_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: 0.5041597337770383
---

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# smids_1x_deit_small_sgd_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: 1.0336
- Accuracy: 0.5042

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0925        | 1.0   | 75   | 1.0713          | 0.4343   |
| 1.0735        | 2.0   | 150  | 1.0692          | 0.4343   |
| 1.0724        | 3.0   | 225  | 1.0673          | 0.4393   |
| 1.0873        | 4.0   | 300  | 1.0654          | 0.4426   |
| 1.1019        | 5.0   | 375  | 1.0637          | 0.4426   |
| 1.0577        | 6.0   | 450  | 1.0620          | 0.4459   |
| 1.0861        | 7.0   | 525  | 1.0604          | 0.4493   |
| 1.0644        | 8.0   | 600  | 1.0588          | 0.4542   |
| 1.0424        | 9.0   | 675  | 1.0573          | 0.4509   |
| 1.0503        | 10.0  | 750  | 1.0559          | 0.4509   |
| 1.0641        | 11.0  | 825  | 1.0545          | 0.4493   |
| 1.0679        | 12.0  | 900  | 1.0532          | 0.4526   |
| 1.0629        | 13.0  | 975  | 1.0520          | 0.4542   |
| 1.0438        | 14.0  | 1050 | 1.0508          | 0.4542   |
| 1.061         | 15.0  | 1125 | 1.0497          | 0.4509   |
| 1.0498        | 16.0  | 1200 | 1.0486          | 0.4509   |
| 1.0521        | 17.0  | 1275 | 1.0475          | 0.4559   |
| 1.0469        | 18.0  | 1350 | 1.0466          | 0.4576   |
| 1.047         | 19.0  | 1425 | 1.0456          | 0.4609   |
| 1.0592        | 20.0  | 1500 | 1.0447          | 0.4659   |
| 1.0668        | 21.0  | 1575 | 1.0439          | 0.4709   |
| 1.0281        | 22.0  | 1650 | 1.0431          | 0.4725   |
| 1.0356        | 23.0  | 1725 | 1.0423          | 0.4775   |
| 1.026         | 24.0  | 1800 | 1.0416          | 0.4775   |
| 1.0466        | 25.0  | 1875 | 1.0409          | 0.4792   |
| 1.0451        | 26.0  | 1950 | 1.0402          | 0.4809   |
| 1.0338        | 27.0  | 2025 | 1.0396          | 0.4859   |
| 1.0199        | 28.0  | 2100 | 1.0390          | 0.4842   |
| 1.0289        | 29.0  | 2175 | 1.0384          | 0.4875   |
| 1.0316        | 30.0  | 2250 | 1.0379          | 0.4908   |
| 1.0446        | 31.0  | 2325 | 1.0374          | 0.4925   |
| 1.0407        | 32.0  | 2400 | 1.0369          | 0.4925   |
| 1.0163        | 33.0  | 2475 | 1.0365          | 0.4925   |
| 1.0508        | 34.0  | 2550 | 1.0361          | 0.4925   |
| 1.024         | 35.0  | 2625 | 1.0358          | 0.4942   |
| 1.0435        | 36.0  | 2700 | 1.0354          | 0.4958   |
| 1.0618        | 37.0  | 2775 | 1.0351          | 0.4958   |
| 1.0365        | 38.0  | 2850 | 1.0349          | 0.4975   |
| 1.0269        | 39.0  | 2925 | 1.0346          | 0.4992   |
| 1.0291        | 40.0  | 3000 | 1.0344          | 0.5008   |
| 1.0505        | 41.0  | 3075 | 1.0342          | 0.5008   |
| 1.0316        | 42.0  | 3150 | 1.0340          | 0.5008   |
| 1.0295        | 43.0  | 3225 | 1.0339          | 0.5008   |
| 1.049         | 44.0  | 3300 | 1.0338          | 0.5008   |
| 1.0556        | 45.0  | 3375 | 1.0337          | 0.5008   |
| 1.0458        | 46.0  | 3450 | 1.0336          | 0.5008   |
| 1.0348        | 47.0  | 3525 | 1.0336          | 0.5008   |
| 1.0496        | 48.0  | 3600 | 1.0336          | 0.5025   |
| 1.0321        | 49.0  | 3675 | 1.0336          | 0.5042   |
| 1.0497        | 50.0  | 3750 | 1.0336          | 0.5042   |


### Framework versions

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