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# SMIDS_10x_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: 1.2002
- Accuracy: 0.9017

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.4332        | 1.0   | 1500  | 0.4164          | 0.8217   |
| 0.3598        | 2.0   | 3000  | 0.3514          | 0.8533   |
| 0.3347        | 3.0   | 4500  | 0.3395          | 0.8817   |
| 0.2704        | 4.0   | 6000  | 0.4247          | 0.8633   |
| 0.2427        | 5.0   | 7500  | 0.3063          | 0.9017   |
| 0.2177        | 6.0   | 9000  | 0.4003          | 0.8783   |
| 0.205         | 7.0   | 10500 | 0.4476          | 0.8867   |
| 0.1883        | 8.0   | 12000 | 0.5146          | 0.8783   |
| 0.0512        | 9.0   | 13500 | 0.5691          | 0.88     |
| 0.0691        | 10.0  | 15000 | 0.6647          | 0.8767   |
| 0.0444        | 11.0  | 16500 | 0.6280          | 0.8767   |
| 0.0235        | 12.0  | 18000 | 0.6553          | 0.8767   |
| 0.0146        | 13.0  | 19500 | 0.6865          | 0.8867   |
| 0.1205        | 14.0  | 21000 | 0.7267          | 0.8917   |
| 0.0008        | 15.0  | 22500 | 0.8826          | 0.8833   |
| 0.0056        | 16.0  | 24000 | 0.6636          | 0.8917   |
| 0.0075        | 17.0  | 25500 | 0.7534          | 0.885    |
| 0.0245        | 18.0  | 27000 | 0.7790          | 0.8883   |
| 0.0152        | 19.0  | 28500 | 1.0096          | 0.8717   |
| 0.0004        | 20.0  | 30000 | 0.7124          | 0.9033   |
| 0.0318        | 21.0  | 31500 | 0.8532          | 0.8917   |
| 0.024         | 22.0  | 33000 | 0.8883          | 0.8867   |
| 0.0002        | 23.0  | 34500 | 0.8975          | 0.875    |
| 0.0001        | 24.0  | 36000 | 0.9276          | 0.8767   |
| 0.0003        | 25.0  | 37500 | 0.7513          | 0.885    |
| 0.0002        | 26.0  | 39000 | 0.8274          | 0.8817   |
| 0.0           | 27.0  | 40500 | 0.8791          | 0.8817   |
| 0.0001        | 28.0  | 42000 | 1.0480          | 0.8833   |
| 0.0           | 29.0  | 43500 | 0.9179          | 0.89     |
| 0.0           | 30.0  | 45000 | 0.9678          | 0.8833   |
| 0.0           | 31.0  | 46500 | 1.1341          | 0.885    |
| 0.0           | 32.0  | 48000 | 1.2024          | 0.875    |
| 0.0           | 33.0  | 49500 | 1.0332          | 0.8833   |
| 0.0           | 34.0  | 51000 | 1.0062          | 0.8917   |
| 0.0           | 35.0  | 52500 | 1.0328          | 0.89     |
| 0.0           | 36.0  | 54000 | 1.1104          | 0.8917   |
| 0.0           | 37.0  | 55500 | 1.0982          | 0.8933   |
| 0.0           | 38.0  | 57000 | 1.1609          | 0.8817   |
| 0.022         | 39.0  | 58500 | 1.2135          | 0.8917   |
| 0.0           | 40.0  | 60000 | 1.1312          | 0.8933   |
| 0.0001        | 41.0  | 61500 | 1.1342          | 0.8967   |
| 0.0           | 42.0  | 63000 | 1.1600          | 0.8967   |
| 0.0           | 43.0  | 64500 | 1.2187          | 0.8917   |
| 0.0           | 44.0  | 66000 | 1.1519          | 0.895    |
| 0.0           | 45.0  | 67500 | 1.1305          | 0.895    |
| 0.0           | 46.0  | 69000 | 1.1554          | 0.8933   |
| 0.0           | 47.0  | 70500 | 1.1888          | 0.895    |
| 0.0           | 48.0  | 72000 | 1.1917          | 0.9      |
| 0.0           | 49.0  | 73500 | 1.1979          | 0.9017   |
| 0.0           | 50.0  | 75000 | 1.2002          | 0.9017   |


### 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_fold3", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9016666666666666, "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