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---
license: apache-2.0
base_model: microsoft/beit-base-patch16-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: beit-base-patch16-224
results: []
---
<!-- 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. -->
# beit-base-patch16-224
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co./microsoft/beit-base-patch16-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3575
- Accuracy: 0.9456
- Precision: 0.9498
- Recall: 0.9456
- F1 Score: 0.9473
## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 45
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| No log | 0.94 | 4 | 0.3212 | 0.8475 | 0.8711 | 0.8475 | 0.7915 |
| No log | 1.88 | 8 | 0.2355 | 0.8983 | 0.8925 | 0.8983 | 0.8937 |
| No log | 2.82 | 12 | 0.3134 | 0.8644 | 0.8834 | 0.8644 | 0.8243 |
| 0.2493 | 4.0 | 17 | 0.2434 | 0.8814 | 0.8962 | 0.8814 | 0.8534 |
| 0.2493 | 4.94 | 21 | 0.3406 | 0.8983 | 0.9094 | 0.8983 | 0.8794 |
| 0.2493 | 5.88 | 25 | 0.1131 | 0.9322 | 0.9300 | 0.9322 | 0.9291 |
| 0.2493 | 6.82 | 29 | 0.1727 | 0.9153 | 0.9435 | 0.9153 | 0.9215 |
| 0.0374 | 8.0 | 34 | 0.6181 | 0.8644 | 0.8834 | 0.8644 | 0.8243 |
| 0.0374 | 8.94 | 38 | 0.3249 | 0.9153 | 0.9125 | 0.9153 | 0.9135 |
| 0.0374 | 9.88 | 42 | 0.5308 | 0.8983 | 0.8934 | 0.8983 | 0.8876 |
| 0.007 | 10.82 | 46 | 0.4767 | 0.9153 | 0.9119 | 0.9153 | 0.9090 |
| 0.007 | 12.0 | 51 | 0.3883 | 0.8983 | 0.8925 | 0.8983 | 0.8937 |
| 0.007 | 12.94 | 55 | 0.3627 | 0.8983 | 0.8934 | 0.8983 | 0.8876 |
| 0.007 | 13.88 | 59 | 0.2783 | 0.9492 | 0.9479 | 0.9492 | 0.9481 |
| 0.0012 | 14.82 | 63 | 0.1934 | 0.9492 | 0.9519 | 0.9492 | 0.9501 |
| 0.0012 | 16.0 | 68 | 0.1670 | 0.9661 | 0.9661 | 0.9661 | 0.9661 |
| 0.0012 | 16.94 | 72 | 0.1783 | 0.9492 | 0.9479 | 0.9492 | 0.9481 |
| 0.0001 | 17.88 | 76 | 0.4825 | 0.9322 | 0.9373 | 0.9322 | 0.9251 |
| 0.0001 | 18.82 | 80 | 0.9010 | 0.8983 | 0.9094 | 0.8983 | 0.8794 |
| 0.0001 | 20.0 | 85 | 0.1802 | 0.9661 | 0.9718 | 0.9661 | 0.9673 |
| 0.0001 | 20.94 | 89 | 0.5658 | 0.9153 | 0.9119 | 0.9153 | 0.9090 |
| 0.0037 | 21.88 | 93 | 0.8331 | 0.9322 | 0.9373 | 0.9322 | 0.9251 |
| 0.0037 | 22.82 | 97 | 0.8074 | 0.9153 | 0.9119 | 0.9153 | 0.9090 |
| 0.0037 | 24.0 | 102 | 0.4763 | 0.8814 | 0.8771 | 0.8814 | 0.8788 |
| 0.0002 | 24.94 | 106 | 0.5553 | 0.9153 | 0.9119 | 0.9153 | 0.9090 |
| 0.0002 | 25.88 | 110 | 0.8220 | 0.9153 | 0.9231 | 0.9153 | 0.9032 |
| 0.0002 | 26.82 | 114 | 0.5367 | 0.9322 | 0.9373 | 0.9322 | 0.9251 |
| 0.0002 | 28.0 | 119 | 0.4401 | 0.9153 | 0.9298 | 0.9153 | 0.9194 |
| 0.0037 | 28.94 | 123 | 0.4138 | 0.9153 | 0.9125 | 0.9153 | 0.9135 |
| 0.0037 | 29.88 | 127 | 0.7232 | 0.8983 | 0.9094 | 0.8983 | 0.8794 |
| 0.0037 | 30.82 | 131 | 0.3690 | 0.9322 | 0.9373 | 0.9322 | 0.9251 |
| 0.0115 | 32.0 | 136 | 0.2730 | 0.9322 | 0.9400 | 0.9322 | 0.9346 |
| 0.0115 | 32.94 | 140 | 0.2101 | 0.9661 | 0.9661 | 0.9661 | 0.9661 |
| 0.0115 | 33.88 | 144 | 0.1814 | 0.9661 | 0.9661 | 0.9661 | 0.9661 |
| 0.0115 | 34.82 | 148 | 0.1641 | 0.9661 | 0.9661 | 0.9661 | 0.9661 |
| 0.0013 | 36.0 | 153 | 0.1600 | 0.9492 | 0.9479 | 0.9492 | 0.9481 |
| 0.0013 | 36.94 | 157 | 0.1709 | 0.9661 | 0.9674 | 0.9661 | 0.9646 |
| 0.0013 | 37.88 | 161 | 0.1913 | 0.9661 | 0.9674 | 0.9661 | 0.9646 |
| 0.0001 | 38.82 | 165 | 0.2047 | 0.9661 | 0.9674 | 0.9661 | 0.9646 |
| 0.0001 | 40.0 | 170 | 0.2030 | 0.9661 | 0.9674 | 0.9661 | 0.9646 |
| 0.0001 | 40.94 | 174 | 0.1960 | 0.9661 | 0.9674 | 0.9661 | 0.9646 |
| 0.0001 | 41.88 | 178 | 0.1936 | 0.9661 | 0.9674 | 0.9661 | 0.9646 |
| 0.0003 | 42.35 | 180 | 0.1934 | 0.9661 | 0.9674 | 0.9661 | 0.9646 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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