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---
license: apache-2.0
base_model: microsoft/beit-large-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: hushem_40x_beit_large_adamax_0001_fold2
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8444444444444444
---
<!-- 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_40x_beit_large_adamax_0001_fold2
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: 1.5515
- Accuracy: 0.8444
## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.0224 | 1.0 | 215 | 0.7690 | 0.8222 |
| 0.0 | 2.0 | 430 | 0.9419 | 0.8222 |
| 0.0 | 3.0 | 645 | 0.9930 | 0.8667 |
| 0.0 | 4.0 | 860 | 0.8917 | 0.8444 |
| 0.0 | 5.0 | 1075 | 0.9011 | 0.8667 |
| 0.0 | 6.0 | 1290 | 0.8682 | 0.8667 |
| 0.0016 | 7.0 | 1505 | 1.2238 | 0.8444 |
| 0.0197 | 8.0 | 1720 | 1.2274 | 0.8667 |
| 0.0027 | 9.0 | 1935 | 1.0944 | 0.8444 |
| 0.0058 | 10.0 | 2150 | 1.9516 | 0.7778 |
| 0.0 | 11.0 | 2365 | 1.8577 | 0.7556 |
| 0.0 | 12.0 | 2580 | 1.7768 | 0.8 |
| 0.0 | 13.0 | 2795 | 1.1199 | 0.7778 |
| 0.0 | 14.0 | 3010 | 1.2644 | 0.8222 |
| 0.0 | 15.0 | 3225 | 0.9150 | 0.8889 |
| 0.0 | 16.0 | 3440 | 0.8728 | 0.8889 |
| 0.0 | 17.0 | 3655 | 0.8904 | 0.8889 |
| 0.0 | 18.0 | 3870 | 0.8975 | 0.8889 |
| 0.0 | 19.0 | 4085 | 0.9193 | 0.8889 |
| 0.0 | 20.0 | 4300 | 0.9261 | 0.8889 |
| 0.0 | 21.0 | 4515 | 1.6757 | 0.8 |
| 0.0 | 22.0 | 4730 | 1.3218 | 0.8444 |
| 0.0 | 23.0 | 4945 | 1.3867 | 0.8222 |
| 0.0 | 24.0 | 5160 | 1.3833 | 0.8444 |
| 0.0 | 25.0 | 5375 | 1.2895 | 0.8444 |
| 0.0 | 26.0 | 5590 | 1.2783 | 0.8667 |
| 0.0 | 27.0 | 5805 | 1.2770 | 0.8667 |
| 0.0 | 28.0 | 6020 | 1.2426 | 0.8667 |
| 0.0 | 29.0 | 6235 | 1.2537 | 0.8667 |
| 0.0 | 30.0 | 6450 | 1.2475 | 0.8667 |
| 0.0 | 31.0 | 6665 | 1.2602 | 0.8667 |
| 0.0 | 32.0 | 6880 | 1.2779 | 0.8667 |
| 0.0 | 33.0 | 7095 | 1.2891 | 0.8667 |
| 0.0 | 34.0 | 7310 | 1.3447 | 0.8444 |
| 0.0 | 35.0 | 7525 | 1.3109 | 0.8667 |
| 0.0 | 36.0 | 7740 | 1.3704 | 0.8667 |
| 0.0 | 37.0 | 7955 | 1.5945 | 0.8 |
| 0.0 | 38.0 | 8170 | 1.5665 | 0.8444 |
| 0.0 | 39.0 | 8385 | 1.4945 | 0.8444 |
| 0.0 | 40.0 | 8600 | 1.4921 | 0.8444 |
| 0.0 | 41.0 | 8815 | 1.5103 | 0.8444 |
| 0.0 | 42.0 | 9030 | 1.5661 | 0.8444 |
| 0.0 | 43.0 | 9245 | 1.5778 | 0.8444 |
| 0.0 | 44.0 | 9460 | 1.5715 | 0.8444 |
| 0.0 | 45.0 | 9675 | 1.5931 | 0.8444 |
| 0.0 | 46.0 | 9890 | 1.5813 | 0.8444 |
| 0.0 | 47.0 | 10105 | 1.5501 | 0.8444 |
| 0.0 | 48.0 | 10320 | 1.5512 | 0.8444 |
| 0.0 | 49.0 | 10535 | 1.5477 | 0.8444 |
| 0.0 | 50.0 | 10750 | 1.5515 | 0.8444 |
### Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2
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