
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# hushem_5x_beit_base_sgd_00001_fold5

This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6137
- Accuracy: 0.2439

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.5748        | 1.0   | 28   | 1.6349          | 0.2439   |
| 1.5498        | 2.0   | 56   | 1.6339          | 0.2439   |
| 1.5458        | 3.0   | 84   | 1.6329          | 0.2439   |
| 1.5997        | 4.0   | 112  | 1.6319          | 0.2439   |
| 1.5518        | 5.0   | 140  | 1.6310          | 0.2439   |
| 1.6078        | 6.0   | 168  | 1.6301          | 0.2439   |
| 1.6054        | 7.0   | 196  | 1.6292          | 0.2439   |
| 1.5635        | 8.0   | 224  | 1.6284          | 0.2439   |
| 1.5412        | 9.0   | 252  | 1.6276          | 0.2439   |
| 1.5684        | 10.0  | 280  | 1.6268          | 0.2439   |
| 1.5211        | 11.0  | 308  | 1.6261          | 0.2439   |
| 1.5857        | 12.0  | 336  | 1.6254          | 0.2439   |
| 1.5804        | 13.0  | 364  | 1.6248          | 0.2439   |
| 1.5778        | 14.0  | 392  | 1.6241          | 0.2439   |
| 1.5905        | 15.0  | 420  | 1.6235          | 0.2439   |
| 1.5552        | 16.0  | 448  | 1.6228          | 0.2439   |
| 1.5712        | 17.0  | 476  | 1.6222          | 0.2439   |
| 1.5113        | 18.0  | 504  | 1.6216          | 0.2439   |
| 1.5441        | 19.0  | 532  | 1.6210          | 0.2439   |
| 1.547         | 20.0  | 560  | 1.6205          | 0.2439   |
| 1.5712        | 21.0  | 588  | 1.6200          | 0.2439   |
| 1.595         | 22.0  | 616  | 1.6195          | 0.2439   |
| 1.6001        | 23.0  | 644  | 1.6190          | 0.2439   |
| 1.6008        | 24.0  | 672  | 1.6185          | 0.2439   |
| 1.5469        | 25.0  | 700  | 1.6181          | 0.2439   |
| 1.567         | 26.0  | 728  | 1.6177          | 0.2439   |
| 1.618         | 27.0  | 756  | 1.6173          | 0.2439   |
| 1.4849        | 28.0  | 784  | 1.6170          | 0.2439   |
| 1.5706        | 29.0  | 812  | 1.6166          | 0.2439   |
| 1.5269        | 30.0  | 840  | 1.6163          | 0.2439   |
| 1.588         | 31.0  | 868  | 1.6160          | 0.2439   |
| 1.5207        | 32.0  | 896  | 1.6157          | 0.2439   |
| 1.5395        | 33.0  | 924  | 1.6155          | 0.2439   |
| 1.5482        | 34.0  | 952  | 1.6152          | 0.2439   |
| 1.6004        | 35.0  | 980  | 1.6150          | 0.2439   |
| 1.5389        | 36.0  | 1008 | 1.6148          | 0.2439   |
| 1.5566        | 37.0  | 1036 | 1.6146          | 0.2439   |
| 1.54          | 38.0  | 1064 | 1.6145          | 0.2439   |
| 1.5715        | 39.0  | 1092 | 1.6143          | 0.2439   |
| 1.5148        | 40.0  | 1120 | 1.6142          | 0.2439   |
| 1.5688        | 41.0  | 1148 | 1.6141          | 0.2439   |
| 1.5803        | 42.0  | 1176 | 1.6140          | 0.2439   |
| 1.5477        | 43.0  | 1204 | 1.6139          | 0.2439   |
| 1.5623        | 44.0  | 1232 | 1.6138          | 0.2439   |
| 1.5648        | 45.0  | 1260 | 1.6137          | 0.2439   |
| 1.5331        | 46.0  | 1288 | 1.6137          | 0.2439   |
| 1.5791        | 47.0  | 1316 | 1.6137          | 0.2439   |
| 1.5282        | 48.0  | 1344 | 1.6137          | 0.2439   |
| 1.5715        | 49.0  | 1372 | 1.6137          | 0.2439   |
| 1.5955        | 50.0  | 1400 | 1.6137          | 0.2439   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["imagefolder"], "metrics": ["accuracy"], "base_model": "microsoft/beit-base-patch16-224", "model-index": [{"name": "hushem_5x_beit_base_sgd_00001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.24390243902439024, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors beit image-classification generated_from_trainer dataset:imagefolder base_model:microsoft/beit-base-patch16-224 license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us