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# SMIDS_1x_beit_large_SGD_lr001_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: 0.2606
- Accuracy: 0.8965

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.8212        | 1.0   | 151  | 0.7777          | 0.6528   |
| 0.6569        | 2.0   | 302  | 0.6156          | 0.7362   |
| 0.5152        | 3.0   | 453  | 0.5328          | 0.7746   |
| 0.4598        | 4.0   | 604  | 0.4778          | 0.8080   |
| 0.4774        | 5.0   | 755  | 0.4436          | 0.8147   |
| 0.4775        | 6.0   | 906  | 0.4102          | 0.8414   |
| 0.3737        | 7.0   | 1057 | 0.3909          | 0.8414   |
| 0.3842        | 8.0   | 1208 | 0.3677          | 0.8514   |
| 0.4178        | 9.0   | 1359 | 0.3619          | 0.8548   |
| 0.3818        | 10.0  | 1510 | 0.3403          | 0.8731   |
| 0.3085        | 11.0  | 1661 | 0.3326          | 0.8648   |
| 0.3182        | 12.0  | 1812 | 0.3203          | 0.8731   |
| 0.3334        | 13.0  | 1963 | 0.3129          | 0.8765   |
| 0.3424        | 14.0  | 2114 | 0.3068          | 0.8831   |
| 0.2984        | 15.0  | 2265 | 0.3014          | 0.8781   |
| 0.3017        | 16.0  | 2416 | 0.2982          | 0.8831   |
| 0.2713        | 17.0  | 2567 | 0.2999          | 0.8748   |
| 0.2409        | 18.0  | 2718 | 0.2908          | 0.8781   |
| 0.2884        | 19.0  | 2869 | 0.2890          | 0.8831   |
| 0.1931        | 20.0  | 3020 | 0.2831          | 0.8881   |
| 0.333         | 21.0  | 3171 | 0.2828          | 0.8915   |
| 0.2397        | 22.0  | 3322 | 0.2806          | 0.8948   |
| 0.2032        | 23.0  | 3473 | 0.2796          | 0.8965   |
| 0.193         | 24.0  | 3624 | 0.2761          | 0.8982   |
| 0.2239        | 25.0  | 3775 | 0.2735          | 0.8965   |
| 0.1926        | 26.0  | 3926 | 0.2739          | 0.8948   |
| 0.2037        | 27.0  | 4077 | 0.2706          | 0.8965   |
| 0.2881        | 28.0  | 4228 | 0.2688          | 0.8965   |
| 0.2189        | 29.0  | 4379 | 0.2690          | 0.8998   |
| 0.196         | 30.0  | 4530 | 0.2685          | 0.8965   |
| 0.2209        | 31.0  | 4681 | 0.2681          | 0.8965   |
| 0.1664        | 32.0  | 4832 | 0.2658          | 0.8982   |
| 0.2442        | 33.0  | 4983 | 0.2637          | 0.8965   |
| 0.1991        | 34.0  | 5134 | 0.2653          | 0.8998   |
| 0.2523        | 35.0  | 5285 | 0.2658          | 0.8998   |
| 0.2272        | 36.0  | 5436 | 0.2639          | 0.8982   |
| 0.2512        | 37.0  | 5587 | 0.2622          | 0.8965   |
| 0.212         | 38.0  | 5738 | 0.2616          | 0.8948   |
| 0.2191        | 39.0  | 5889 | 0.2618          | 0.8965   |
| 0.2026        | 40.0  | 6040 | 0.2609          | 0.8965   |
| 0.2204        | 41.0  | 6191 | 0.2607          | 0.8965   |
| 0.1746        | 42.0  | 6342 | 0.2615          | 0.8965   |
| 0.1257        | 43.0  | 6493 | 0.2622          | 0.8982   |
| 0.1329        | 44.0  | 6644 | 0.2617          | 0.8965   |
| 0.199         | 45.0  | 6795 | 0.2614          | 0.8965   |
| 0.2535        | 46.0  | 6946 | 0.2609          | 0.8965   |
| 0.1937        | 47.0  | 7097 | 0.2608          | 0.8965   |
| 0.0974        | 48.0  | 7248 | 0.2608          | 0.8965   |
| 0.2566        | 49.0  | 7399 | 0.2606          | 0.8965   |
| 0.1659        | 50.0  | 7550 | 0.2606          | 0.8965   |


### 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_SGD_lr001_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.8964941569282137, "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