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# hushem_5x_beit_base_sgd_001_fold4

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: 0.9066
- Accuracy: 0.7143

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.529         | 1.0   | 28   | 1.4303          | 0.2857   |
| 1.4725        | 2.0   | 56   | 1.3788          | 0.2857   |
| 1.3888        | 3.0   | 84   | 1.3402          | 0.3571   |
| 1.357         | 4.0   | 112  | 1.3238          | 0.3333   |
| 1.2619        | 5.0   | 140  | 1.3109          | 0.3571   |
| 1.2354        | 6.0   | 168  | 1.2864          | 0.4286   |
| 1.2209        | 7.0   | 196  | 1.2694          | 0.4524   |
| 1.2033        | 8.0   | 224  | 1.2439          | 0.4524   |
| 1.1737        | 9.0   | 252  | 1.2291          | 0.4762   |
| 1.1593        | 10.0  | 280  | 1.2131          | 0.4762   |
| 1.1467        | 11.0  | 308  | 1.1977          | 0.4762   |
| 1.1374        | 12.0  | 336  | 1.1819          | 0.5      |
| 1.1253        | 13.0  | 364  | 1.1622          | 0.4762   |
| 1.1026        | 14.0  | 392  | 1.1551          | 0.4762   |
| 1.0893        | 15.0  | 420  | 1.1365          | 0.4762   |
| 1.0476        | 16.0  | 448  | 1.1177          | 0.4762   |
| 1.0789        | 17.0  | 476  | 1.1065          | 0.4762   |
| 1.0455        | 18.0  | 504  | 1.0907          | 0.4762   |
| 1.0028        | 19.0  | 532  | 1.0816          | 0.4762   |
| 1.004         | 20.0  | 560  | 1.0638          | 0.4762   |
| 0.967         | 21.0  | 588  | 1.0579          | 0.5      |
| 0.9933        | 22.0  | 616  | 1.0403          | 0.5      |
| 0.9551        | 23.0  | 644  | 1.0323          | 0.5714   |
| 0.9924        | 24.0  | 672  | 1.0183          | 0.5952   |
| 0.9236        | 25.0  | 700  | 1.0095          | 0.6190   |
| 0.9232        | 26.0  | 728  | 0.9951          | 0.6190   |
| 0.9574        | 27.0  | 756  | 1.0017          | 0.6190   |
| 0.9076        | 28.0  | 784  | 0.9866          | 0.6429   |
| 0.9034        | 29.0  | 812  | 0.9711          | 0.6429   |
| 0.8865        | 30.0  | 840  | 0.9696          | 0.6667   |
| 0.9168        | 31.0  | 868  | 0.9618          | 0.6667   |
| 0.8917        | 32.0  | 896  | 0.9532          | 0.6905   |
| 0.901         | 33.0  | 924  | 0.9560          | 0.6667   |
| 0.8911        | 34.0  | 952  | 0.9475          | 0.6667   |
| 0.9166        | 35.0  | 980  | 0.9435          | 0.7143   |
| 0.9177        | 36.0  | 1008 | 0.9323          | 0.7143   |
| 0.8498        | 37.0  | 1036 | 0.9279          | 0.7143   |
| 0.8848        | 38.0  | 1064 | 0.9240          | 0.7143   |
| 0.8498        | 39.0  | 1092 | 0.9206          | 0.7143   |
| 0.8193        | 40.0  | 1120 | 0.9192          | 0.7143   |
| 0.8443        | 41.0  | 1148 | 0.9102          | 0.7143   |
| 0.8576        | 42.0  | 1176 | 0.9108          | 0.7143   |
| 0.8916        | 43.0  | 1204 | 0.9094          | 0.7143   |
| 0.8299        | 44.0  | 1232 | 0.9082          | 0.7143   |
| 0.8298        | 45.0  | 1260 | 0.9062          | 0.7143   |
| 0.8683        | 46.0  | 1288 | 0.9063          | 0.7143   |
| 0.8298        | 47.0  | 1316 | 0.9065          | 0.7143   |
| 0.8412        | 48.0  | 1344 | 0.9065          | 0.7143   |
| 0.8333        | 49.0  | 1372 | 0.9066          | 0.7143   |
| 0.8603        | 50.0  | 1400 | 0.9066          | 0.7143   |


### 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_001_fold4", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.7142857142857143, "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