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# SMIDS_1x_beit_large_Adamax_lr00001_fold1

This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6619
- Accuracy: 0.8932

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.2997        | 1.0   | 151  | 0.2750          | 0.8915   |
| 0.2468        | 2.0   | 302  | 0.3023          | 0.8798   |
| 0.2014        | 3.0   | 453  | 0.2796          | 0.9065   |
| 0.0903        | 4.0   | 604  | 0.3191          | 0.9048   |
| 0.0439        | 5.0   | 755  | 0.3330          | 0.9065   |
| 0.0904        | 6.0   | 906  | 0.4060          | 0.9098   |
| 0.052         | 7.0   | 1057 | 0.5287          | 0.8831   |
| 0.0029        | 8.0   | 1208 | 0.5404          | 0.8982   |
| 0.0354        | 9.0   | 1359 | 0.5641          | 0.8831   |
| 0.0008        | 10.0  | 1510 | 0.5148          | 0.8982   |
| 0.0181        | 11.0  | 1661 | 0.5857          | 0.8865   |
| 0.0006        | 12.0  | 1812 | 0.5503          | 0.9032   |
| 0.066         | 13.0  | 1963 | 0.5724          | 0.9048   |
| 0.0232        | 14.0  | 2114 | 0.6086          | 0.8965   |
| 0.0001        | 15.0  | 2265 | 0.6147          | 0.8898   |
| 0.0001        | 16.0  | 2416 | 0.5756          | 0.9015   |
| 0.0004        | 17.0  | 2567 | 0.6109          | 0.8932   |
| 0.0002        | 18.0  | 2718 | 0.6123          | 0.8982   |
| 0.0001        | 19.0  | 2869 | 0.6599          | 0.8898   |
| 0.0001        | 20.0  | 3020 | 0.6253          | 0.9015   |
| 0.0454        | 21.0  | 3171 | 0.5882          | 0.9048   |
| 0.0136        | 22.0  | 3322 | 0.6186          | 0.8865   |
| 0.0           | 23.0  | 3473 | 0.6426          | 0.8965   |
| 0.0411        | 24.0  | 3624 | 0.6111          | 0.9048   |
| 0.0058        | 25.0  | 3775 | 0.6157          | 0.8998   |
| 0.0           | 26.0  | 3926 | 0.6202          | 0.8965   |
| 0.0           | 27.0  | 4077 | 0.6696          | 0.8982   |
| 0.0282        | 28.0  | 4228 | 0.6369          | 0.8982   |
| 0.0001        | 29.0  | 4379 | 0.6319          | 0.8915   |
| 0.0           | 30.0  | 4530 | 0.6423          | 0.8998   |
| 0.0162        | 31.0  | 4681 | 0.6538          | 0.8965   |
| 0.022         | 32.0  | 4832 | 0.6521          | 0.8982   |
| 0.0088        | 33.0  | 4983 | 0.6607          | 0.8915   |
| 0.0299        | 34.0  | 5134 | 0.6459          | 0.8965   |
| 0.0018        | 35.0  | 5285 | 0.6498          | 0.8932   |
| 0.0           | 36.0  | 5436 | 0.6462          | 0.8948   |
| 0.0174        | 37.0  | 5587 | 0.6536          | 0.8965   |
| 0.0           | 38.0  | 5738 | 0.6392          | 0.8948   |
| 0.0176        | 39.0  | 5889 | 0.6355          | 0.8982   |
| 0.0           | 40.0  | 6040 | 0.6370          | 0.9032   |
| 0.0           | 41.0  | 6191 | 0.6339          | 0.8965   |
| 0.0           | 42.0  | 6342 | 0.6563          | 0.8982   |
| 0.0028        | 43.0  | 6493 | 0.6561          | 0.8948   |
| 0.0006        | 44.0  | 6644 | 0.6613          | 0.8948   |
| 0.0           | 45.0  | 6795 | 0.6604          | 0.8965   |
| 0.0001        | 46.0  | 6946 | 0.6591          | 0.8915   |
| 0.0302        | 47.0  | 7097 | 0.6613          | 0.8948   |
| 0.0111        | 48.0  | 7248 | 0.6607          | 0.8948   |
| 0.0009        | 49.0  | 7399 | 0.6616          | 0.8915   |
| 0.0001        | 50.0  | 7550 | 0.6619          | 0.8932   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-large-patch16-224", "model-index": [{"name": "SMIDS_1x_beit_large_Adamax_lr00001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8931552587646077, "name": "Accuracy"}]}]}]}
transformers pytorch beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-large-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us