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# SMIDS_10x_beit_large_adamax_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: 0.9422
- Accuracy: 0.9032

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.3876        | 1.0   | 1501  | 0.4265          | 0.8364   |
| 0.344         | 2.0   | 3002  | 0.4724          | 0.8247   |
| 0.2007        | 3.0   | 4503  | 0.4176          | 0.8631   |
| 0.1219        | 4.0   | 6004  | 0.4004          | 0.8915   |
| 0.1402        | 5.0   | 7505  | 0.3131          | 0.9015   |
| 0.1013        | 6.0   | 9006  | 0.5013          | 0.8664   |
| 0.1302        | 7.0   | 10507 | 0.4787          | 0.8798   |
| 0.1256        | 8.0   | 12008 | 0.5626          | 0.8681   |
| 0.1023        | 9.0   | 13509 | 0.5661          | 0.8898   |
| 0.1043        | 10.0  | 15010 | 0.4190          | 0.8865   |
| 0.1679        | 11.0  | 16511 | 0.5228          | 0.8831   |
| 0.0311        | 12.0  | 18012 | 0.7520          | 0.8648   |
| 0.0919        | 13.0  | 19513 | 0.4869          | 0.9032   |
| 0.0428        | 14.0  | 21014 | 0.7835          | 0.8998   |
| 0.0042        | 15.0  | 22515 | 0.6651          | 0.8781   |
| 0.0006        | 16.0  | 24016 | 0.6863          | 0.8982   |
| 0.0615        | 17.0  | 25517 | 0.6866          | 0.8998   |
| 0.0191        | 18.0  | 27018 | 0.4910          | 0.9149   |
| 0.0398        | 19.0  | 28519 | 0.7049          | 0.8848   |
| 0.0218        | 20.0  | 30020 | 0.7020          | 0.8982   |
| 0.0002        | 21.0  | 31521 | 0.8018          | 0.8915   |
| 0.0015        | 22.0  | 33022 | 0.8164          | 0.8865   |
| 0.0008        | 23.0  | 34523 | 0.7636          | 0.9149   |
| 0.0016        | 24.0  | 36024 | 0.8518          | 0.8848   |
| 0.0013        | 25.0  | 37525 | 0.6365          | 0.9098   |
| 0.0043        | 26.0  | 39026 | 0.6562          | 0.8965   |
| 0.0           | 27.0  | 40527 | 0.6964          | 0.9065   |
| 0.0           | 28.0  | 42028 | 0.8883          | 0.8982   |
| 0.0001        | 29.0  | 43529 | 0.6305          | 0.9098   |
| 0.0           | 30.0  | 45030 | 0.6628          | 0.8932   |
| 0.0           | 31.0  | 46531 | 0.7753          | 0.9032   |
| 0.0           | 32.0  | 48032 | 0.7377          | 0.9098   |
| 0.0008        | 33.0  | 49533 | 0.8111          | 0.9082   |
| 0.0           | 34.0  | 51034 | 0.7210          | 0.9149   |
| 0.0628        | 35.0  | 52535 | 0.6853          | 0.9132   |
| 0.0           | 36.0  | 54036 | 0.8580          | 0.9015   |
| 0.0           | 37.0  | 55537 | 0.8215          | 0.9082   |
| 0.0           | 38.0  | 57038 | 0.9523          | 0.9082   |
| 0.0           | 39.0  | 58539 | 0.8719          | 0.9032   |
| 0.0           | 40.0  | 60040 | 0.8707          | 0.9149   |
| 0.0           | 41.0  | 61541 | 0.9109          | 0.9065   |
| 0.0           | 42.0  | 63042 | 0.8678          | 0.9098   |
| 0.0           | 43.0  | 64543 | 0.9191          | 0.9082   |
| 0.0           | 44.0  | 66044 | 0.9287          | 0.9082   |
| 0.0           | 45.0  | 67545 | 0.9228          | 0.9132   |
| 0.0052        | 46.0  | 69046 | 0.9072          | 0.9065   |
| 0.0           | 47.0  | 70547 | 0.9431          | 0.9032   |
| 0.0           | 48.0  | 72048 | 0.9415          | 0.9032   |
| 0.0           | 49.0  | 73549 | 0.9373          | 0.9048   |
| 0.0           | 50.0  | 75050 | 0.9422          | 0.9032   |


### 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_fold1", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9031719532554258, "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