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# SMIDS_1x_beit_large_RMSProp_lr001_fold2

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: 0.9220
- Accuracy: 0.7521

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.9498        | 1.0   | 150  | 0.8990          | 0.5158   |
| 0.8816        | 2.0   | 300  | 1.0007          | 0.3827   |
| 0.7606        | 3.0   | 450  | 0.8227          | 0.5541   |
| 0.8052        | 4.0   | 600  | 0.7691          | 0.5724   |
| 0.78          | 5.0   | 750  | 0.7684          | 0.5807   |
| 0.8097        | 6.0   | 900  | 0.7713          | 0.5790   |
| 0.766         | 7.0   | 1050 | 0.7644          | 0.6156   |
| 0.7307        | 8.0   | 1200 | 0.7396          | 0.6456   |
| 0.7459        | 9.0   | 1350 | 0.7408          | 0.6556   |
| 0.8596        | 10.0  | 1500 | 0.9231          | 0.4859   |
| 0.7939        | 11.0  | 1650 | 0.7646          | 0.6306   |
| 0.7433        | 12.0  | 1800 | 0.7487          | 0.6606   |
| 0.7279        | 13.0  | 1950 | 0.7297          | 0.6805   |
| 0.6981        | 14.0  | 2100 | 0.7145          | 0.6805   |
| 0.7711        | 15.0  | 2250 | 0.7497          | 0.6705   |
| 0.6803        | 16.0  | 2400 | 0.7038          | 0.6672   |
| 0.7799        | 17.0  | 2550 | 0.6830          | 0.6755   |
| 0.6097        | 18.0  | 2700 | 0.6881          | 0.6772   |
| 0.6549        | 19.0  | 2850 | 0.7037          | 0.6755   |
| 0.5875        | 20.0  | 3000 | 0.7273          | 0.6789   |
| 0.6024        | 21.0  | 3150 | 0.7187          | 0.6839   |
| 0.6066        | 22.0  | 3300 | 0.7045          | 0.6772   |
| 0.7299        | 23.0  | 3450 | 0.6591          | 0.7038   |
| 0.6283        | 24.0  | 3600 | 0.7121          | 0.6922   |
| 0.6562        | 25.0  | 3750 | 0.6768          | 0.6755   |
| 0.4812        | 26.0  | 3900 | 0.6652          | 0.7105   |
| 0.5655        | 27.0  | 4050 | 0.6358          | 0.7271   |
| 0.5403        | 28.0  | 4200 | 0.6317          | 0.7271   |
| 0.5519        | 29.0  | 4350 | 0.6627          | 0.7088   |
| 0.5252        | 30.0  | 4500 | 0.6470          | 0.7138   |
| 0.5093        | 31.0  | 4650 | 0.6491          | 0.7304   |
| 0.5659        | 32.0  | 4800 | 0.6787          | 0.7205   |
| 0.5187        | 33.0  | 4950 | 0.7015          | 0.7171   |
| 0.4004        | 34.0  | 5100 | 0.6741          | 0.7471   |
| 0.4609        | 35.0  | 5250 | 0.6836          | 0.7438   |
| 0.4011        | 36.0  | 5400 | 0.6762          | 0.7504   |
| 0.4153        | 37.0  | 5550 | 0.6845          | 0.7188   |
| 0.3838        | 38.0  | 5700 | 0.7046          | 0.7637   |
| 0.4086        | 39.0  | 5850 | 0.6681          | 0.7587   |
| 0.4241        | 40.0  | 6000 | 0.6928          | 0.7554   |
| 0.3111        | 41.0  | 6150 | 0.7136          | 0.7654   |
| 0.3572        | 42.0  | 6300 | 0.7229          | 0.7671   |
| 0.4613        | 43.0  | 6450 | 0.7939          | 0.7454   |
| 0.284         | 44.0  | 6600 | 0.7751          | 0.7571   |
| 0.3663        | 45.0  | 6750 | 0.8187          | 0.7737   |
| 0.3374        | 46.0  | 6900 | 0.8704          | 0.7604   |
| 0.4269        | 47.0  | 7050 | 0.8562          | 0.7521   |
| 0.3321        | 48.0  | 7200 | 0.9213          | 0.7571   |
| 0.2814        | 49.0  | 7350 | 0.9184          | 0.7587   |
| 0.263         | 50.0  | 7500 | 0.9220          | 0.7521   |


### 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_1x_beit_large_RMSProp_lr001_fold2", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7520798668885191, "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