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# hushem_1x_deit_tiny_adamax_00001_fold2

This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3630
- Accuracy: 0.5333

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 6    | 1.3933          | 0.2889   |
| 1.4502        | 2.0   | 12   | 1.3758          | 0.2889   |
| 1.4502        | 3.0   | 18   | 1.3846          | 0.1556   |
| 1.1864        | 4.0   | 24   | 1.3867          | 0.2      |
| 1.0417        | 5.0   | 30   | 1.4200          | 0.2222   |
| 1.0417        | 6.0   | 36   | 1.4398          | 0.2667   |
| 0.8998        | 7.0   | 42   | 1.4309          | 0.2667   |
| 0.8998        | 8.0   | 48   | 1.4422          | 0.2889   |
| 0.802         | 9.0   | 54   | 1.4525          | 0.3111   |
| 0.7173        | 10.0  | 60   | 1.4451          | 0.3333   |
| 0.7173        | 11.0  | 66   | 1.4170          | 0.3556   |
| 0.6327        | 12.0  | 72   | 1.4262          | 0.3778   |
| 0.6327        | 13.0  | 78   | 1.4500          | 0.3778   |
| 0.5705        | 14.0  | 84   | 1.4362          | 0.3778   |
| 0.4928        | 15.0  | 90   | 1.4119          | 0.3778   |
| 0.4928        | 16.0  | 96   | 1.4031          | 0.4      |
| 0.4272        | 17.0  | 102  | 1.4009          | 0.4      |
| 0.4272        | 18.0  | 108  | 1.4134          | 0.4      |
| 0.3882        | 19.0  | 114  | 1.4007          | 0.4      |
| 0.3396        | 20.0  | 120  | 1.3936          | 0.4      |
| 0.3396        | 21.0  | 126  | 1.3916          | 0.4222   |
| 0.2975        | 22.0  | 132  | 1.3801          | 0.4222   |
| 0.2975        | 23.0  | 138  | 1.3854          | 0.4222   |
| 0.2664        | 24.0  | 144  | 1.3827          | 0.4444   |
| 0.2292        | 25.0  | 150  | 1.3826          | 0.4444   |
| 0.2292        | 26.0  | 156  | 1.3717          | 0.4667   |
| 0.2136        | 27.0  | 162  | 1.3670          | 0.4667   |
| 0.2136        | 28.0  | 168  | 1.3720          | 0.4667   |
| 0.1873        | 29.0  | 174  | 1.3622          | 0.4667   |
| 0.1666        | 30.0  | 180  | 1.3494          | 0.5111   |
| 0.1666        | 31.0  | 186  | 1.3586          | 0.4889   |
| 0.1595        | 32.0  | 192  | 1.3677          | 0.5111   |
| 0.1595        | 33.0  | 198  | 1.3760          | 0.5111   |
| 0.1486        | 34.0  | 204  | 1.3711          | 0.5111   |
| 0.1401        | 35.0  | 210  | 1.3652          | 0.5111   |
| 0.1401        | 36.0  | 216  | 1.3610          | 0.5333   |
| 0.1317        | 37.0  | 222  | 1.3597          | 0.5333   |
| 0.1317        | 38.0  | 228  | 1.3618          | 0.5333   |
| 0.1202        | 39.0  | 234  | 1.3633          | 0.5333   |
| 0.122         | 40.0  | 240  | 1.3628          | 0.5333   |
| 0.122         | 41.0  | 246  | 1.3631          | 0.5333   |
| 0.1214        | 42.0  | 252  | 1.3630          | 0.5333   |
| 0.1214        | 43.0  | 258  | 1.3630          | 0.5333   |
| 0.1203        | 44.0  | 264  | 1.3630          | 0.5333   |
| 0.1185        | 45.0  | 270  | 1.3630          | 0.5333   |
| 0.1185        | 46.0  | 276  | 1.3630          | 0.5333   |
| 0.1174        | 47.0  | 282  | 1.3630          | 0.5333   |
| 0.1174        | 48.0  | 288  | 1.3630          | 0.5333   |
| 0.1152        | 49.0  | 294  | 1.3630          | 0.5333   |
| 0.1204        | 50.0  | 300  | 1.3630          | 0.5333   |


### 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-tiny-patch16-224", "model-index": [{"name": "hushem_1x_deit_tiny_adamax_00001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.5333333333333333, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors vit image-classification generated_from_trainer dataset:imagefolder base_model:facebook/deit-tiny-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us