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# SMIDS_10x_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: 0.2962
- Accuracy: 0.9132

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3316        | 1.0   | 1501  | 0.4067          | 0.8280   |
| 0.3688        | 2.0   | 3002  | 0.3377          | 0.8564   |
| 0.2049        | 3.0   | 4503  | 0.3078          | 0.8614   |
| 0.2194        | 4.0   | 6004  | 0.2846          | 0.8748   |
| 0.2064        | 5.0   | 7505  | 0.2809          | 0.8731   |
| 0.2254        | 6.0   | 9006  | 0.2750          | 0.8748   |
| 0.2134        | 7.0   | 10507 | 0.2656          | 0.8848   |
| 0.1746        | 8.0   | 12008 | 0.2716          | 0.8798   |
| 0.1872        | 9.0   | 13509 | 0.2600          | 0.8898   |
| 0.1858        | 10.0  | 15010 | 0.2677          | 0.8932   |
| 0.247         | 11.0  | 16511 | 0.2634          | 0.8998   |
| 0.1351        | 12.0  | 18012 | 0.2695          | 0.8865   |
| 0.2065        | 13.0  | 19513 | 0.2566          | 0.9048   |
| 0.1329        | 14.0  | 21014 | 0.2613          | 0.8915   |
| 0.1505        | 15.0  | 22515 | 0.2769          | 0.8915   |
| 0.2178        | 16.0  | 24016 | 0.2676          | 0.8965   |
| 0.2657        | 17.0  | 25517 | 0.2611          | 0.9032   |
| 0.172         | 18.0  | 27018 | 0.2566          | 0.9098   |
| 0.225         | 19.0  | 28519 | 0.2739          | 0.8998   |
| 0.1839        | 20.0  | 30020 | 0.2652          | 0.9032   |
| 0.1118        | 21.0  | 31521 | 0.2661          | 0.9098   |
| 0.1104        | 22.0  | 33022 | 0.2666          | 0.9132   |
| 0.1005        | 23.0  | 34523 | 0.2823          | 0.9015   |
| 0.1392        | 24.0  | 36024 | 0.2761          | 0.9048   |
| 0.1243        | 25.0  | 37525 | 0.2713          | 0.9098   |
| 0.1633        | 26.0  | 39026 | 0.2851          | 0.9032   |
| 0.1868        | 27.0  | 40527 | 0.2905          | 0.9048   |
| 0.1746        | 28.0  | 42028 | 0.2807          | 0.9082   |
| 0.1578        | 29.0  | 43529 | 0.2869          | 0.9132   |
| 0.1353        | 30.0  | 45030 | 0.2843          | 0.9082   |
| 0.1003        | 31.0  | 46531 | 0.2813          | 0.9065   |
| 0.2073        | 32.0  | 48032 | 0.2825          | 0.9149   |
| 0.1739        | 33.0  | 49533 | 0.2901          | 0.9149   |
| 0.0902        | 34.0  | 51034 | 0.2874          | 0.9082   |
| 0.1485        | 35.0  | 52535 | 0.2910          | 0.9132   |
| 0.2016        | 36.0  | 54036 | 0.2933          | 0.9115   |
| 0.1874        | 37.0  | 55537 | 0.2831          | 0.9115   |
| 0.0771        | 38.0  | 57038 | 0.2899          | 0.9132   |
| 0.0972        | 39.0  | 58539 | 0.2872          | 0.9115   |
| 0.2048        | 40.0  | 60040 | 0.2990          | 0.9132   |
| 0.0602        | 41.0  | 61541 | 0.2962          | 0.9115   |
| 0.1073        | 42.0  | 63042 | 0.2898          | 0.9115   |
| 0.0669        | 43.0  | 64543 | 0.2930          | 0.9115   |
| 0.0954        | 44.0  | 66044 | 0.2940          | 0.9165   |
| 0.1502        | 45.0  | 67545 | 0.2938          | 0.9132   |
| 0.19          | 46.0  | 69046 | 0.2951          | 0.9132   |
| 0.0733        | 47.0  | 70547 | 0.2953          | 0.9132   |
| 0.0525        | 48.0  | 72048 | 0.2953          | 0.9132   |
| 0.0293        | 49.0  | 73549 | 0.2956          | 0.9149   |
| 0.1247        | 50.0  | 75050 | 0.2962          | 0.9132   |


### 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_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": 0.9131886477462438, "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