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# SMIDS_1x_beit_large_Adamax_lr001_fold3

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: 1.6838
- Accuracy: 0.7767

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8321        | 1.0   | 150  | 0.8536          | 0.535    |
| 0.8599        | 2.0   | 300  | 0.8102          | 0.6067   |
| 0.7554        | 3.0   | 450  | 0.7266          | 0.6567   |
| 0.7342        | 4.0   | 600  | 0.7097          | 0.675    |
| 0.6349        | 5.0   | 750  | 0.7148          | 0.6417   |
| 0.6435        | 6.0   | 900  | 0.6706          | 0.7      |
| 0.6189        | 7.0   | 1050 | 0.6446          | 0.7083   |
| 0.4874        | 8.0   | 1200 | 0.6504          | 0.745    |
| 0.595         | 9.0   | 1350 | 0.6568          | 0.7217   |
| 0.5419        | 10.0  | 1500 | 0.5712          | 0.7567   |
| 0.5363        | 11.0  | 1650 | 0.6584          | 0.74     |
| 0.4962        | 12.0  | 1800 | 0.6097          | 0.745    |
| 0.3922        | 13.0  | 1950 | 0.5607          | 0.7767   |
| 0.4444        | 14.0  | 2100 | 0.5839          | 0.76     |
| 0.3998        | 15.0  | 2250 | 0.5366          | 0.7683   |
| 0.3639        | 16.0  | 2400 | 0.6969          | 0.7617   |
| 0.328         | 17.0  | 2550 | 0.6773          | 0.75     |
| 0.2688        | 18.0  | 2700 | 0.7945          | 0.7617   |
| 0.3205        | 19.0  | 2850 | 0.6082          | 0.7867   |
| 0.324         | 20.0  | 3000 | 0.6774          | 0.7883   |
| 0.2264        | 21.0  | 3150 | 0.8910          | 0.765    |
| 0.186         | 22.0  | 3300 | 0.8928          | 0.7833   |
| 0.3246        | 23.0  | 3450 | 0.7219          | 0.805    |
| 0.3439        | 24.0  | 3600 | 0.7566          | 0.79     |
| 0.0761        | 25.0  | 3750 | 0.8677          | 0.7833   |
| 0.1651        | 26.0  | 3900 | 1.1806          | 0.775    |
| 0.1603        | 27.0  | 4050 | 1.2247          | 0.7883   |
| 0.1148        | 28.0  | 4200 | 1.0679          | 0.7917   |
| 0.1245        | 29.0  | 4350 | 1.2681          | 0.8083   |
| 0.0905        | 30.0  | 4500 | 1.3116          | 0.8033   |
| 0.069         | 31.0  | 4650 | 1.3475          | 0.7933   |
| 0.0502        | 32.0  | 4800 | 1.1061          | 0.79     |
| 0.1093        | 33.0  | 4950 | 1.3642          | 0.7933   |
| 0.0181        | 34.0  | 5100 | 1.5613          | 0.7767   |
| 0.0262        | 35.0  | 5250 | 1.6223          | 0.7967   |
| 0.0317        | 36.0  | 5400 | 1.5822          | 0.7833   |
| 0.0051        | 37.0  | 5550 | 1.5131          | 0.79     |
| 0.0023        | 38.0  | 5700 | 1.7662          | 0.79     |
| 0.0035        | 39.0  | 5850 | 1.5322          | 0.7933   |
| 0.0315        | 40.0  | 6000 | 1.6949          | 0.7833   |
| 0.0256        | 41.0  | 6150 | 1.7013          | 0.79     |
| 0.0004        | 42.0  | 6300 | 1.6885          | 0.7833   |
| 0.0195        | 43.0  | 6450 | 1.7932          | 0.775    |
| 0.011         | 44.0  | 6600 | 1.7136          | 0.775    |
| 0.0441        | 45.0  | 6750 | 1.7382          | 0.7817   |
| 0.016         | 46.0  | 6900 | 1.6190          | 0.7767   |
| 0.0072        | 47.0  | 7050 | 1.7210          | 0.7767   |
| 0.0001        | 48.0  | 7200 | 1.7697          | 0.7817   |
| 0.0476        | 49.0  | 7350 | 1.6703          | 0.7817   |
| 0.0044        | 50.0  | 7500 | 1.6838          | 0.7767   |


### 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_lr001_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7766666666666666, "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