
<!-- 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_10x_beit_large_Adamax_lr00001_fold5

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: 0.4801
- Accuracy: 0.9024

## 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: 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1485        | 1.0   | 110  | 0.3876          | 0.8293   |
| 0.0124        | 2.0   | 220  | 0.3902          | 0.8049   |
| 0.0165        | 3.0   | 330  | 0.3114          | 0.9024   |
| 0.0055        | 4.0   | 440  | 0.3226          | 0.9024   |
| 0.001         | 5.0   | 550  | 0.4581          | 0.8537   |
| 0.0002        | 6.0   | 660  | 0.4454          | 0.9024   |
| 0.0001        | 7.0   | 770  | 0.3935          | 0.9024   |
| 0.0003        | 8.0   | 880  | 0.4211          | 0.9024   |
| 0.0001        | 9.0   | 990  | 0.3966          | 0.9024   |
| 0.0013        | 10.0  | 1100 | 0.3808          | 0.9024   |
| 0.0001        | 11.0  | 1210 | 0.4157          | 0.9024   |
| 0.0001        | 12.0  | 1320 | 0.4117          | 0.9024   |
| 0.0001        | 13.0  | 1430 | 0.4220          | 0.9024   |
| 0.0           | 14.0  | 1540 | 0.4081          | 0.9024   |
| 0.0           | 15.0  | 1650 | 0.4108          | 0.9024   |
| 0.0002        | 16.0  | 1760 | 0.4139          | 0.9024   |
| 0.0           | 17.0  | 1870 | 0.4359          | 0.9024   |
| 0.0           | 18.0  | 1980 | 0.5158          | 0.9024   |
| 0.0001        | 19.0  | 2090 | 0.4957          | 0.9024   |
| 0.0001        | 20.0  | 2200 | 0.4771          | 0.9024   |
| 0.0           | 21.0  | 2310 | 0.4625          | 0.9024   |
| 0.0           | 22.0  | 2420 | 0.3939          | 0.9024   |
| 0.0           | 23.0  | 2530 | 0.4635          | 0.9024   |
| 0.0           | 24.0  | 2640 | 0.5179          | 0.9024   |
| 0.0           | 25.0  | 2750 | 0.4194          | 0.9024   |
| 0.0           | 26.0  | 2860 | 0.4070          | 0.9024   |
| 0.0           | 27.0  | 2970 | 0.4357          | 0.9024   |
| 0.0003        | 28.0  | 3080 | 0.4331          | 0.9024   |
| 0.0           | 29.0  | 3190 | 0.4833          | 0.9024   |
| 0.0           | 30.0  | 3300 | 0.4690          | 0.9024   |
| 0.0           | 31.0  | 3410 | 0.4199          | 0.9024   |
| 0.0           | 32.0  | 3520 | 0.4877          | 0.9024   |
| 0.0           | 33.0  | 3630 | 0.4253          | 0.9024   |
| 0.0           | 34.0  | 3740 | 0.4420          | 0.9024   |
| 0.0           | 35.0  | 3850 | 0.4600          | 0.9024   |
| 0.0           | 36.0  | 3960 | 0.4362          | 0.9024   |
| 0.0001        | 37.0  | 4070 | 0.4445          | 0.9024   |
| 0.0           | 38.0  | 4180 | 0.4565          | 0.9024   |
| 0.0           | 39.0  | 4290 | 0.4095          | 0.9024   |
| 0.0           | 40.0  | 4400 | 0.4200          | 0.9024   |
| 0.0           | 41.0  | 4510 | 0.4116          | 0.9024   |
| 0.0           | 42.0  | 4620 | 0.4373          | 0.9024   |
| 0.0           | 43.0  | 4730 | 0.4409          | 0.9024   |
| 0.0           | 44.0  | 4840 | 0.4845          | 0.9024   |
| 0.0           | 45.0  | 4950 | 0.4771          | 0.9024   |
| 0.0           | 46.0  | 5060 | 0.4804          | 0.9024   |
| 0.0           | 47.0  | 5170 | 0.4726          | 0.9024   |
| 0.0           | 48.0  | 5280 | 0.4785          | 0.9024   |
| 0.0           | 49.0  | 5390 | 0.4802          | 0.9024   |
| 0.0           | 50.0  | 5500 | 0.4801          | 0.9024   |


### 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": "HUSHEM_10x_beit_large_Adamax_lr00001_fold5", "results": [{"task": {"type": "image-classification", "name": "Image Classification"}, "dataset": {"name": "imagefolder", "type": "imagefolder", "config": "default", "split": "test", "args": "default"}, "metrics": [{"type": "accuracy", "value": 0.9024390243902439, "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