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# SMIDS_10x_beit_large_adamax_lr001_fold5

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: 0.9899
- Accuracy: 0.9167

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4398        | 1.0   | 1500  | 0.4051          | 0.845    |
| 0.2937        | 2.0   | 3000  | 0.3092          | 0.8883   |
| 0.2871        | 3.0   | 4500  | 0.3274          | 0.8933   |
| 0.1444        | 4.0   | 6000  | 0.4680          | 0.8667   |
| 0.3386        | 5.0   | 7500  | 0.3047          | 0.8883   |
| 0.2008        | 6.0   | 9000  | 0.3667          | 0.8867   |
| 0.1726        | 7.0   | 10500 | 0.3919          | 0.8917   |
| 0.157         | 8.0   | 12000 | 0.3808          | 0.9067   |
| 0.0607        | 9.0   | 13500 | 0.5086          | 0.8817   |
| 0.0111        | 10.0  | 15000 | 0.4453          | 0.92     |
| 0.0542        | 11.0  | 16500 | 0.4738          | 0.8883   |
| 0.0141        | 12.0  | 18000 | 0.5424          | 0.9083   |
| 0.0019        | 13.0  | 19500 | 0.6384          | 0.9      |
| 0.0158        | 14.0  | 21000 | 0.6288          | 0.9      |
| 0.06          | 15.0  | 22500 | 0.6173          | 0.9033   |
| 0.0038        | 16.0  | 24000 | 0.5868          | 0.91     |
| 0.0311        | 17.0  | 25500 | 0.7416          | 0.9017   |
| 0.0004        | 18.0  | 27000 | 0.7447          | 0.895    |
| 0.0168        | 19.0  | 28500 | 0.6675          | 0.91     |
| 0.0218        | 20.0  | 30000 | 0.7953          | 0.9      |
| 0.0004        | 21.0  | 31500 | 0.8713          | 0.8983   |
| 0.0035        | 22.0  | 33000 | 0.8038          | 0.8983   |
| 0.0276        | 23.0  | 34500 | 0.6672          | 0.9033   |
| 0.0053        | 24.0  | 36000 | 0.6475          | 0.9133   |
| 0.0001        | 25.0  | 37500 | 0.7267          | 0.92     |
| 0.0           | 26.0  | 39000 | 0.7697          | 0.9117   |
| 0.0           | 27.0  | 40500 | 0.8046          | 0.92     |
| 0.0338        | 28.0  | 42000 | 0.7651          | 0.9083   |
| 0.0           | 29.0  | 43500 | 0.7104          | 0.91     |
| 0.0001        | 30.0  | 45000 | 0.6766          | 0.9183   |
| 0.0           | 31.0  | 46500 | 0.7626          | 0.925    |
| 0.0           | 32.0  | 48000 | 0.9298          | 0.9083   |
| 0.0008        | 33.0  | 49500 | 1.0871          | 0.9      |
| 0.0           | 34.0  | 51000 | 0.8239          | 0.905    |
| 0.0           | 35.0  | 52500 | 0.7935          | 0.9167   |
| 0.0           | 36.0  | 54000 | 0.9161          | 0.9183   |
| 0.0           | 37.0  | 55500 | 0.8789          | 0.9083   |
| 0.0           | 38.0  | 57000 | 1.0323          | 0.905    |
| 0.0           | 39.0  | 58500 | 0.9568          | 0.915    |
| 0.0           | 40.0  | 60000 | 0.8580          | 0.9217   |
| 0.0           | 41.0  | 61500 | 0.9224          | 0.91     |
| 0.0           | 42.0  | 63000 | 1.0047          | 0.9033   |
| 0.0           | 43.0  | 64500 | 1.0227          | 0.9067   |
| 0.0           | 44.0  | 66000 | 0.9914          | 0.9083   |
| 0.0           | 45.0  | 67500 | 0.9515          | 0.915    |
| 0.0           | 46.0  | 69000 | 0.9472          | 0.9167   |
| 0.0           | 47.0  | 70500 | 0.9640          | 0.9167   |
| 0.0           | 48.0  | 72000 | 0.9832          | 0.9183   |
| 0.0           | 49.0  | 73500 | 0.9894          | 0.9167   |
| 0.0           | 50.0  | 75000 | 0.9899          | 0.9167   |


### 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": "microsoft/beit-large-patch16-224", "model-index": [{"name": "SMIDS_10x_beit_large_adamax_lr001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9166666666666666, "name": "Accuracy"}]}]}]}
transformers safetensors 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