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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: 0.3752
- Accuracy: 0.9388
- Precision: 0.9451
- Recall: 0.9388
- F1 Score: 0.9412
## 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 | 0.9412 | 4 | 0.3599 | 0.8644 | 0.8831 | 0.8644 | 0.8152 |
| No log | 1.8824 | 8 | 0.2752 | 0.8983 | 0.8983 | 0.8983 | 0.8983 |
| No log | 2.8235 | 12 | 0.1735 | 0.9322 | 0.9293 | 0.9322 | 0.9286 |
| 0.2978 | 4.0 | 17 | 0.1745 | 0.9153 | 0.9311 | 0.9153 | 0.9200 |
| 0.2978 | 4.9412 | 21 | 0.1888 | 0.9153 | 0.9196 | 0.9153 | 0.9171 |
| 0.2978 | 5.8824 | 25 | 0.2819 | 0.8983 | 0.9092 | 0.8983 | 0.9024 |
| 0.2978 | 6.8235 | 29 | 0.5332 | 0.9153 | 0.9230 | 0.9153 | 0.9010 |
| 0.0283 | 8.0 | 34 | 0.5418 | 0.9153 | 0.9311 | 0.9153 | 0.9200 |
| 0.0283 | 8.9412 | 38 | 0.6494 | 0.8983 | 0.9092 | 0.8983 | 0.8758 |
| 0.0283 | 9.8824 | 42 | 0.5615 | 0.9153 | 0.9455 | 0.9153 | 0.9222 |
| 0.0061 | 10.8235 | 46 | 0.8767 | 0.8983 | 0.8910 | 0.8983 | 0.8857 |
| 0.0061 | 12.0 | 51 | 0.3859 | 0.9492 | 0.9619 | 0.9492 | 0.9520 |
| 0.0061 | 12.9412 | 55 | 0.4550 | 0.9322 | 0.9322 | 0.9322 | 0.9322 |
| 0.0061 | 13.8824 | 59 | 0.4314 | 0.9492 | 0.9477 | 0.9492 | 0.9479 |
| 0.01 | 14.8235 | 63 | 0.4127 | 0.9492 | 0.9619 | 0.9492 | 0.9520 |
| 0.01 | 16.0 | 68 | 0.3285 | 0.9492 | 0.9477 | 0.9492 | 0.9479 |
| 0.01 | 16.9412 | 72 | 0.3180 | 0.9492 | 0.9477 | 0.9492 | 0.9479 |
| 0.0076 | 17.8824 | 76 | 0.4482 | 0.9322 | 0.9293 | 0.9322 | 0.9286 |
| 0.0076 | 18.8235 | 80 | 0.4437 | 0.9322 | 0.9322 | 0.9322 | 0.9322 |
| 0.0076 | 20.0 | 85 | 0.4819 | 0.9322 | 0.9322 | 0.9322 | 0.9322 |
| 0.0076 | 20.9412 | 89 | 0.5133 | 0.9322 | 0.9293 | 0.9322 | 0.9286 |
| 0.0003 | 21.8824 | 93 | 0.4540 | 0.9492 | 0.9477 | 0.9492 | 0.9479 |
| 0.0003 | 22.8235 | 97 | 0.3857 | 0.9153 | 0.9196 | 0.9153 | 0.9171 |
| 0.0003 | 24.0 | 102 | 0.4077 | 0.8983 | 0.9092 | 0.8983 | 0.9024 |
| 0.0028 | 24.9412 | 106 | 0.3956 | 0.9492 | 0.9477 | 0.9492 | 0.9479 |
| 0.0028 | 25.8824 | 110 | 0.4671 | 0.9322 | 0.9293 | 0.9322 | 0.9286 |
| 0.0028 | 26.8235 | 114 | 0.3811 | 0.9322 | 0.9322 | 0.9322 | 0.9322 |
| 0.0028 | 28.0 | 119 | 0.3700 | 0.9322 | 0.9322 | 0.9322 | 0.9322 |
| 0.0006 | 28.9412 | 123 | 0.4028 | 0.9322 | 0.9322 | 0.9322 | 0.9322 |
| 0.0006 | 29.8824 | 127 | 0.6924 | 0.9153 | 0.9106 | 0.9153 | 0.9080 |
| 0.0006 | 30.8235 | 131 | 0.6949 | 0.9153 | 0.9106 | 0.9153 | 0.9080 |
| 0.0033 | 32.0 | 136 | 0.5889 | 0.9153 | 0.9120 | 0.9153 | 0.9132 |
| 0.0033 | 32.9412 | 140 | 0.5128 | 0.9322 | 0.9322 | 0.9322 | 0.9322 |
| 0.0033 | 33.8824 | 144 | 0.4411 | 0.9492 | 0.9522 | 0.9492 | 0.9502 |
| 0.0033 | 34.8235 | 148 | 0.4420 | 0.9492 | 0.9522 | 0.9492 | 0.9502 |
| 0.0013 | 36.0 | 153 | 0.5616 | 0.9322 | 0.9322 | 0.9322 | 0.9322 |
| 0.0013 | 36.9412 | 157 | 0.6365 | 0.9153 | 0.9120 | 0.9153 | 0.9132 |
| 0.0013 | 37.8824 | 161 | 0.6695 | 0.9153 | 0.9120 | 0.9153 | 0.9132 |
| 0.0001 | 38.8235 | 165 | 0.6846 | 0.9153 | 0.9120 | 0.9153 | 0.9132 |
| 0.0001 | 40.0 | 170 | 0.6930 | 0.9153 | 0.9120 | 0.9153 | 0.9132 |
| 0.0001 | 40.9412 | 174 | 0.6958 | 0.9153 | 0.9120 | 0.9153 | 0.9132 |
| 0.0001 | 41.8824 | 178 | 0.6967 | 0.9153 | 0.9120 | 0.9153 | 0.9132 |
| 0.0044 | 42.3529 | 180 | 0.6952 | 0.9153 | 0.9120 | 0.9153 | 0.9132 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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