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# SMIDS_10x_deit_base_rmsprop_lr001_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: 0.9582
- Accuracy: 0.7930

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.8515        | 1.0   | 751   | 0.8330          | 0.5342   |
| 0.6936        | 2.0   | 1502  | 0.7630          | 0.6678   |
| 0.6774        | 3.0   | 2253  | 0.7096          | 0.6711   |
| 0.6301        | 4.0   | 3004  | 0.7501          | 0.6494   |
| 0.6992        | 5.0   | 3755  | 0.7094          | 0.6294   |
| 0.7043        | 6.0   | 4506  | 0.7345          | 0.6828   |
| 0.5883        | 7.0   | 5257  | 0.6223          | 0.7262   |
| 0.6139        | 8.0   | 6008  | 0.7213          | 0.6711   |
| 0.5811        | 9.0   | 6759  | 0.5704          | 0.7429   |
| 0.5592        | 10.0  | 7510  | 0.5613          | 0.7646   |
| 0.5727        | 11.0  | 8261  | 0.6227          | 0.6962   |
| 0.5403        | 12.0  | 9012  | 0.5750          | 0.7379   |
| 0.5298        | 13.0  | 9763  | 0.5500          | 0.7496   |
| 0.5019        | 14.0  | 10514 | 0.5395          | 0.7546   |
| 0.4898        | 15.0  | 11265 | 0.5632          | 0.7446   |
| 0.529         | 16.0  | 12016 | 0.5634          | 0.7462   |
| 0.545         | 17.0  | 12767 | 0.6061          | 0.7229   |
| 0.4356        | 18.0  | 13518 | 0.6530          | 0.7245   |
| 0.4907        | 19.0  | 14269 | 0.5764          | 0.7563   |
| 0.4825        | 20.0  | 15020 | 0.5714          | 0.7446   |
| 0.4334        | 21.0  | 15771 | 0.5992          | 0.7679   |
| 0.4541        | 22.0  | 16522 | 0.5550          | 0.7579   |
| 0.3881        | 23.0  | 17273 | 0.5259          | 0.7830   |
| 0.4651        | 24.0  | 18024 | 0.5806          | 0.7679   |
| 0.4279        | 25.0  | 18775 | 0.5390          | 0.7863   |
| 0.4478        | 26.0  | 19526 | 0.5452          | 0.7880   |
| 0.4226        | 27.0  | 20277 | 0.5248          | 0.8047   |
| 0.454         | 28.0  | 21028 | 0.5393          | 0.7846   |
| 0.3477        | 29.0  | 21779 | 0.6005          | 0.7846   |
| 0.3064        | 30.0  | 22530 | 0.5263          | 0.7980   |
| 0.3677        | 31.0  | 23281 | 0.5375          | 0.7997   |
| 0.3999        | 32.0  | 24032 | 0.5275          | 0.7896   |
| 0.3912        | 33.0  | 24783 | 0.5281          | 0.7913   |
| 0.3386        | 34.0  | 25534 | 0.5880          | 0.7896   |
| 0.2921        | 35.0  | 26285 | 0.5798          | 0.7896   |
| 0.3619        | 36.0  | 27036 | 0.5678          | 0.7980   |
| 0.3418        | 37.0  | 27787 | 0.5897          | 0.8047   |
| 0.2711        | 38.0  | 28538 | 0.6835          | 0.7880   |
| 0.2337        | 39.0  | 29289 | 0.6470          | 0.7863   |
| 0.337         | 40.0  | 30040 | 0.7079          | 0.7746   |
| 0.2462        | 41.0  | 30791 | 0.6908          | 0.7846   |
| 0.234         | 42.0  | 31542 | 0.7227          | 0.7963   |
| 0.3294        | 43.0  | 32293 | 0.7153          | 0.7963   |
| 0.2144        | 44.0  | 33044 | 0.7350          | 0.7947   |
| 0.2103        | 45.0  | 33795 | 0.7521          | 0.7963   |
| 0.2636        | 46.0  | 34546 | 0.8169          | 0.7947   |
| 0.1919        | 47.0  | 35297 | 0.8666          | 0.7997   |
| 0.2045        | 48.0  | 36048 | 0.8829          | 0.8047   |
| 0.1543        | 49.0  | 36799 | 0.9383          | 0.7997   |
| 0.1199        | 50.0  | 37550 | 0.9582          | 0.7930   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0
- Datasets 2.14.6
- 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": "SMIDS_10x_deit_base_rmsprop_lr001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7929883138564274, "name": "Accuracy"}]}]}]}
transformers 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