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# hushem_5x_deit_base_adamax_001_fold2

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: 5.7416
- Accuracy: 0.4889

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.4053        | 1.0   | 27   | 1.3685          | 0.3111   |
| 1.3925        | 2.0   | 54   | 3.6868          | 0.2889   |
| 1.2318        | 3.0   | 81   | 1.5265          | 0.3333   |
| 1.1218        | 4.0   | 108  | 1.3720          | 0.3778   |
| 0.9389        | 5.0   | 135  | 1.3538          | 0.4444   |
| 0.8792        | 6.0   | 162  | 1.1885          | 0.4444   |
| 0.8387        | 7.0   | 189  | 1.3407          | 0.4889   |
| 0.7915        | 8.0   | 216  | 1.2361          | 0.4222   |
| 0.79          | 9.0   | 243  | 1.2485          | 0.4667   |
| 0.7076        | 10.0  | 270  | 1.6183          | 0.5333   |
| 0.6051        | 11.0  | 297  | 1.7700          | 0.4889   |
| 0.5603        | 12.0  | 324  | 1.7918          | 0.3556   |
| 0.6144        | 13.0  | 351  | 2.1767          | 0.5556   |
| 0.5279        | 14.0  | 378  | 1.6851          | 0.3778   |
| 0.3562        | 15.0  | 405  | 2.1689          | 0.4444   |
| 0.3897        | 16.0  | 432  | 2.2755          | 0.4667   |
| 0.4523        | 17.0  | 459  | 2.3235          | 0.4222   |
| 0.5055        | 18.0  | 486  | 2.6282          | 0.5556   |
| 0.2707        | 19.0  | 513  | 2.3398          | 0.5333   |
| 0.4827        | 20.0  | 540  | 2.5025          | 0.5111   |
| 0.2449        | 21.0  | 567  | 2.2455          | 0.4667   |
| 0.3199        | 22.0  | 594  | 3.8583          | 0.5333   |
| 0.2715        | 23.0  | 621  | 2.9016          | 0.5556   |
| 0.2241        | 24.0  | 648  | 2.9266          | 0.4444   |
| 0.1264        | 25.0  | 675  | 3.0321          | 0.4222   |
| 0.1028        | 26.0  | 702  | 3.8439          | 0.5778   |
| 0.2082        | 27.0  | 729  | 3.7749          | 0.5333   |
| 0.2344        | 28.0  | 756  | 3.4616          | 0.5333   |
| 0.0842        | 29.0  | 783  | 3.5970          | 0.5111   |
| 0.0483        | 30.0  | 810  | 4.3955          | 0.5111   |
| 0.1454        | 31.0  | 837  | 3.9120          | 0.5556   |
| 0.0972        | 32.0  | 864  | 3.9463          | 0.4889   |
| 0.014         | 33.0  | 891  | 4.4955          | 0.4889   |
| 0.0007        | 34.0  | 918  | 5.1958          | 0.5111   |
| 0.0273        | 35.0  | 945  | 5.0022          | 0.4889   |
| 0.0071        | 36.0  | 972  | 4.9340          | 0.5333   |
| 0.0003        | 37.0  | 999  | 5.2310          | 0.4889   |
| 0.0004        | 38.0  | 1026 | 5.5820          | 0.4889   |
| 0.0001        | 39.0  | 1053 | 5.6491          | 0.4889   |
| 0.0001        | 40.0  | 1080 | 5.6867          | 0.4889   |
| 0.0001        | 41.0  | 1107 | 5.7009          | 0.4889   |
| 0.0001        | 42.0  | 1134 | 5.7115          | 0.4889   |
| 0.0           | 43.0  | 1161 | 5.7213          | 0.4889   |
| 0.0001        | 44.0  | 1188 | 5.7289          | 0.4889   |
| 0.0001        | 45.0  | 1215 | 5.7342          | 0.4889   |
| 0.0           | 46.0  | 1242 | 5.7384          | 0.4889   |
| 0.0           | 47.0  | 1269 | 5.7406          | 0.4889   |
| 0.0           | 48.0  | 1296 | 5.7416          | 0.4889   |
| 0.0001        | 49.0  | 1323 | 5.7416          | 0.4889   |
| 0.0           | 50.0  | 1350 | 5.7416          | 0.4889   |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "facebook/deit-base-patch16-224", "model-index": [{"name": "hushem_5x_deit_base_adamax_001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.4888888888888889, "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