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# hushem_1x_deit_small_adamax_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: 2.9089
- Accuracy: 0.5854

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.5709          | 0.2683   |
| 1.6365        | 2.0   | 12   | 1.3231          | 0.3171   |
| 1.6365        | 3.0   | 18   | 1.0858          | 0.4878   |
| 1.2777        | 4.0   | 24   | 1.0527          | 0.4634   |
| 1.0819        | 5.0   | 30   | 2.4025          | 0.4878   |
| 1.0819        | 6.0   | 36   | 1.0776          | 0.6098   |
| 1.1957        | 7.0   | 42   | 1.2491          | 0.4878   |
| 1.1957        | 8.0   | 48   | 1.2390          | 0.4878   |
| 1.0582        | 9.0   | 54   | 2.4696          | 0.3659   |
| 0.9645        | 10.0  | 60   | 0.9800          | 0.6585   |
| 0.9645        | 11.0  | 66   | 1.4465          | 0.4878   |
| 0.7158        | 12.0  | 72   | 1.3709          | 0.4146   |
| 0.7158        | 13.0  | 78   | 1.8787          | 0.5610   |
| 0.4707        | 14.0  | 84   | 2.2003          | 0.4878   |
| 0.3746        | 15.0  | 90   | 2.7652          | 0.4390   |
| 0.3746        | 16.0  | 96   | 1.4738          | 0.6098   |
| 0.3815        | 17.0  | 102  | 2.1297          | 0.4878   |
| 0.3815        | 18.0  | 108  | 2.7358          | 0.4634   |
| 0.2562        | 19.0  | 114  | 2.1602          | 0.6341   |
| 0.215         | 20.0  | 120  | 2.4495          | 0.5122   |
| 0.215         | 21.0  | 126  | 2.2161          | 0.5366   |
| 0.0855        | 22.0  | 132  | 2.6756          | 0.5610   |
| 0.0855        | 23.0  | 138  | 3.4355          | 0.5366   |
| 0.0976        | 24.0  | 144  | 2.8453          | 0.6098   |
| 0.0588        | 25.0  | 150  | 2.9043          | 0.5854   |
| 0.0588        | 26.0  | 156  | 3.0589          | 0.4878   |
| 0.0051        | 27.0  | 162  | 2.7256          | 0.6098   |
| 0.0051        | 28.0  | 168  | 2.6655          | 0.6098   |
| 0.0018        | 29.0  | 174  | 2.6795          | 0.6098   |
| 0.005         | 30.0  | 180  | 2.7568          | 0.6098   |
| 0.005         | 31.0  | 186  | 2.8042          | 0.6098   |
| 0.0004        | 32.0  | 192  | 2.8224          | 0.6098   |
| 0.0004        | 33.0  | 198  | 2.8428          | 0.6098   |
| 0.0002        | 34.0  | 204  | 2.8628          | 0.5854   |
| 0.0002        | 35.0  | 210  | 2.8783          | 0.5854   |
| 0.0002        | 36.0  | 216  | 2.8881          | 0.5854   |
| 0.0002        | 37.0  | 222  | 2.8950          | 0.5854   |
| 0.0002        | 38.0  | 228  | 2.9002          | 0.5854   |
| 0.0002        | 39.0  | 234  | 2.9045          | 0.5854   |
| 0.0002        | 40.0  | 240  | 2.9071          | 0.5854   |
| 0.0002        | 41.0  | 246  | 2.9084          | 0.5854   |
| 0.0001        | 42.0  | 252  | 2.9089          | 0.5854   |
| 0.0001        | 43.0  | 258  | 2.9089          | 0.5854   |
| 0.0002        | 44.0  | 264  | 2.9089          | 0.5854   |
| 0.0001        | 45.0  | 270  | 2.9089          | 0.5854   |
| 0.0001        | 46.0  | 276  | 2.9089          | 0.5854   |
| 0.0002        | 47.0  | 282  | 2.9089          | 0.5854   |
| 0.0002        | 48.0  | 288  | 2.9089          | 0.5854   |
| 0.0001        | 49.0  | 294  | 2.9089          | 0.5854   |
| 0.0001        | 50.0  | 300  | 2.9089          | 0.5854   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-small-patch16-224", "model-index": [{"name": "hushem_1x_deit_small_adamax_001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5853658536585366, "name": "Accuracy"}]}]}]}
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