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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: 0.8528
- Accuracy: 0.8268
- Precision: 0.8303
- Recall: 0.8268
- F1 Score: 0.8283
## 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: 48
- eval_batch_size: 48
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 192
- 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 | 0.8 | 2 | 0.6993 | 0.5882 | 0.5390 | 0.5882 | 0.5541 |
| No log | 2.0 | 5 | 0.5971 | 0.6863 | 0.6806 | 0.6863 | 0.6033 |
| No log | 2.8 | 7 | 0.5306 | 0.8039 | 0.8000 | 0.8039 | 0.8006 |
| No log | 4.0 | 10 | 0.4828 | 0.7255 | 0.7229 | 0.7255 | 0.6859 |
| No log | 4.8 | 12 | 0.3812 | 0.7843 | 0.7786 | 0.7843 | 0.7784 |
| 0.5413 | 6.0 | 15 | 0.5268 | 0.7451 | 0.7461 | 0.7451 | 0.7141 |
| 0.5413 | 6.8 | 17 | 0.5349 | 0.7451 | 0.8556 | 0.7451 | 0.7502 |
| 0.5413 | 8.0 | 20 | 0.4120 | 0.8039 | 0.8485 | 0.8039 | 0.7756 |
| 0.5413 | 8.8 | 22 | 0.3156 | 0.8039 | 0.8003 | 0.8039 | 0.7963 |
| 0.5413 | 10.0 | 25 | 0.3217 | 0.8039 | 0.8061 | 0.8039 | 0.7909 |
| 0.5413 | 10.8 | 27 | 0.5161 | 0.7843 | 0.7870 | 0.7843 | 0.7664 |
| 0.0919 | 12.0 | 30 | 0.3677 | 0.8431 | 0.8498 | 0.8431 | 0.8451 |
| 0.0919 | 12.8 | 32 | 0.4631 | 0.8431 | 0.8407 | 0.8431 | 0.8405 |
| 0.0919 | 14.0 | 35 | 0.5001 | 0.8235 | 0.8214 | 0.8235 | 0.8221 |
| 0.0919 | 14.8 | 37 | 0.4489 | 0.8431 | 0.8431 | 0.8431 | 0.8431 |
| 0.0919 | 16.0 | 40 | 0.5892 | 0.7843 | 0.7799 | 0.7843 | 0.7731 |
| 0.0919 | 16.8 | 42 | 0.6579 | 0.7843 | 0.7799 | 0.7843 | 0.7731 |
| 0.006 | 18.0 | 45 | 0.7038 | 0.7843 | 0.7799 | 0.7843 | 0.7731 |
| 0.006 | 18.8 | 47 | 0.5864 | 0.8627 | 0.8737 | 0.8627 | 0.8651 |
| 0.006 | 20.0 | 50 | 0.5488 | 0.8627 | 0.8737 | 0.8627 | 0.8651 |
| 0.006 | 20.8 | 52 | 0.6651 | 0.8039 | 0.8003 | 0.8039 | 0.7963 |
| 0.006 | 22.0 | 55 | 0.6265 | 0.8039 | 0.8000 | 0.8039 | 0.8006 |
| 0.006 | 22.8 | 57 | 0.5229 | 0.8627 | 0.8653 | 0.8627 | 0.8637 |
| 0.0048 | 24.0 | 60 | 0.5421 | 0.8627 | 0.8653 | 0.8627 | 0.8637 |
| 0.0048 | 24.8 | 62 | 0.6335 | 0.8235 | 0.8205 | 0.8235 | 0.8187 |
| 0.0048 | 26.0 | 65 | 1.0379 | 0.8039 | 0.8201 | 0.8039 | 0.7841 |
| 0.0048 | 26.8 | 67 | 0.9758 | 0.8235 | 0.8366 | 0.8235 | 0.8089 |
| 0.0048 | 28.0 | 70 | 0.6117 | 0.8235 | 0.8205 | 0.8235 | 0.8187 |
| 0.0048 | 28.8 | 72 | 0.5403 | 0.8627 | 0.8613 | 0.8627 | 0.8617 |
| 0.0063 | 30.0 | 75 | 0.6469 | 0.8431 | 0.8407 | 0.8431 | 0.8405 |
| 0.0063 | 30.8 | 77 | 0.7014 | 0.8235 | 0.8205 | 0.8235 | 0.8187 |
| 0.0063 | 32.0 | 80 | 0.7514 | 0.8235 | 0.8205 | 0.8235 | 0.8187 |
| 0.0063 | 32.8 | 82 | 0.7771 | 0.8235 | 0.8248 | 0.8235 | 0.8144 |
| 0.0063 | 34.0 | 85 | 0.7599 | 0.8039 | 0.8003 | 0.8039 | 0.7963 |
| 0.0063 | 34.8 | 87 | 0.7554 | 0.8039 | 0.8003 | 0.8039 | 0.7963 |
| 0.0045 | 36.0 | 90 | 0.7308 | 0.8039 | 0.8003 | 0.8039 | 0.7963 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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