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# hushem_1x_deit_base_adamax_001_fold1

This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 4.0186
- 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: 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    | 1.5701          | 0.2444   |
| 1.7784        | 2.0   | 12   | 1.4475          | 0.2444   |
| 1.7784        | 3.0   | 18   | 1.5245          | 0.2444   |
| 1.3959        | 4.0   | 24   | 1.4708          | 0.4222   |
| 1.2593        | 5.0   | 30   | 1.4970          | 0.2889   |
| 1.2593        | 6.0   | 36   | 2.3855          | 0.2444   |
| 1.1884        | 7.0   | 42   | 1.0899          | 0.5333   |
| 1.1884        | 8.0   | 48   | 1.5303          | 0.3778   |
| 1.0528        | 9.0   | 54   | 1.8879          | 0.2667   |
| 0.9521        | 10.0  | 60   | 1.5051          | 0.3556   |
| 0.9521        | 11.0  | 66   | 1.7383          | 0.4222   |
| 0.832         | 12.0  | 72   | 1.4982          | 0.4667   |
| 0.832         | 13.0  | 78   | 2.2428          | 0.4222   |
| 0.6131        | 14.0  | 84   | 2.0924          | 0.4667   |
| 0.7375        | 15.0  | 90   | 1.9680          | 0.3778   |
| 0.7375        | 16.0  | 96   | 2.1272          | 0.4      |
| 0.3749        | 17.0  | 102  | 2.6064          | 0.4222   |
| 0.3749        | 18.0  | 108  | 3.2946          | 0.4      |
| 0.1952        | 19.0  | 114  | 3.4322          | 0.4      |
| 0.1436        | 20.0  | 120  | 3.6588          | 0.4222   |
| 0.1436        | 21.0  | 126  | 2.5255          | 0.4889   |
| 0.198         | 22.0  | 132  | 4.0901          | 0.3778   |
| 0.198         | 23.0  | 138  | 3.7265          | 0.4444   |
| 0.1826        | 24.0  | 144  | 2.5207          | 0.5333   |
| 0.0757        | 25.0  | 150  | 3.1947          | 0.4667   |
| 0.0757        | 26.0  | 156  | 2.8055          | 0.5333   |
| 0.0579        | 27.0  | 162  | 2.7690          | 0.5333   |
| 0.0579        | 28.0  | 168  | 3.0584          | 0.5333   |
| 0.0219        | 29.0  | 174  | 2.7699          | 0.6      |
| 0.0037        | 30.0  | 180  | 3.6076          | 0.5556   |
| 0.0037        | 31.0  | 186  | 4.1981          | 0.4667   |
| 0.0005        | 32.0  | 192  | 4.2123          | 0.5111   |
| 0.0005        | 33.0  | 198  | 4.1138          | 0.4889   |
| 0.0004        | 34.0  | 204  | 4.0577          | 0.5333   |
| 0.0002        | 35.0  | 210  | 4.0352          | 0.5333   |
| 0.0002        | 36.0  | 216  | 4.0255          | 0.5333   |
| 0.0002        | 37.0  | 222  | 4.0206          | 0.5333   |
| 0.0002        | 38.0  | 228  | 4.0191          | 0.5333   |
| 0.0001        | 39.0  | 234  | 4.0188          | 0.5333   |
| 0.0001        | 40.0  | 240  | 4.0186          | 0.5333   |
| 0.0001        | 41.0  | 246  | 4.0185          | 0.5333   |
| 0.0001        | 42.0  | 252  | 4.0186          | 0.5333   |
| 0.0001        | 43.0  | 258  | 4.0186          | 0.5333   |
| 0.0001        | 44.0  | 264  | 4.0186          | 0.5333   |
| 0.0001        | 45.0  | 270  | 4.0186          | 0.5333   |
| 0.0001        | 46.0  | 276  | 4.0186          | 0.5333   |
| 0.0001        | 47.0  | 282  | 4.0186          | 0.5333   |
| 0.0001        | 48.0  | 288  | 4.0186          | 0.5333   |
| 0.0001        | 49.0  | 294  | 4.0186          | 0.5333   |
| 0.0001        | 50.0  | 300  | 4.0186          | 0.5333   |


### Framework versions

- Transformers 4.35.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-base-patch16-224", "model-index": [{"name": "hushem_1x_deit_base_adamax_001_fold1", "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-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us