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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: 0.5338
- Accuracy: 0.7165
- Precision: 0.7127
- Recall: 0.7165
- F1 Score: 0.7139
## 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 | 0.7127 | 0.5686 | 0.3992 | 0.5686 | 0.4691 |
| No log | 2.0 | 5 | 0.5967 | 0.6863 | 0.7053 | 0.6863 | 0.6139 |
| No log | 2.8 | 7 | 0.5384 | 0.7843 | 0.7801 | 0.7843 | 0.7792 |
| No log | 4.0 | 10 | 0.6429 | 0.6078 | 0.6547 | 0.6078 | 0.6164 |
| No log | 4.8 | 12 | 0.6321 | 0.7255 | 0.7205 | 0.7255 | 0.7011 |
| No log | 6.0 | 15 | 0.6473 | 0.7255 | 0.7164 | 0.7255 | 0.7095 |
| No log | 6.8 | 17 | 0.7575 | 0.6863 | 0.6694 | 0.6863 | 0.6584 |
| No log | 8.0 | 20 | 0.9926 | 0.7255 | 0.7312 | 0.7255 | 0.6908 |
| No log | 8.8 | 22 | 0.9139 | 0.7255 | 0.7205 | 0.7255 | 0.7011 |
| No log | 10.0 | 25 | 1.0884 | 0.7059 | 0.6937 | 0.7059 | 0.6845 |
| No log | 10.8 | 27 | 1.2796 | 0.7451 | 0.7521 | 0.7451 | 0.7179 |
| 0.287 | 12.0 | 30 | 1.3326 | 0.6863 | 0.6704 | 0.6863 | 0.6680 |
| 0.287 | 12.8 | 32 | 1.5649 | 0.7255 | 0.7205 | 0.7255 | 0.7011 |
| 0.287 | 14.0 | 35 | 1.7452 | 0.7255 | 0.7205 | 0.7255 | 0.7011 |
| 0.287 | 14.8 | 37 | 1.7826 | 0.7255 | 0.7205 | 0.7255 | 0.7011 |
| 0.287 | 16.0 | 40 | 1.9538 | 0.7255 | 0.7312 | 0.7255 | 0.6908 |
| 0.287 | 16.8 | 42 | 1.8850 | 0.6863 | 0.6694 | 0.6863 | 0.6584 |
| 0.287 | 18.0 | 45 | 1.7633 | 0.6863 | 0.6739 | 0.6863 | 0.6756 |
| 0.287 | 18.8 | 47 | 1.7925 | 0.7059 | 0.6940 | 0.7059 | 0.6925 |
| 0.287 | 20.0 | 50 | 2.1156 | 0.7255 | 0.7312 | 0.7255 | 0.6908 |
| 0.287 | 20.8 | 52 | 2.0156 | 0.7255 | 0.7205 | 0.7255 | 0.7011 |
| 0.287 | 22.0 | 55 | 1.8471 | 0.7255 | 0.7164 | 0.7255 | 0.7095 |
| 0.287 | 22.8 | 57 | 1.7831 | 0.7647 | 0.7593 | 0.7647 | 0.7567 |
| 0.0041 | 24.0 | 60 | 1.7628 | 0.7647 | 0.7593 | 0.7647 | 0.7567 |
| 0.0041 | 24.8 | 62 | 1.8077 | 0.7451 | 0.7382 | 0.7451 | 0.7335 |
| 0.0041 | 26.0 | 65 | 1.8068 | 0.7843 | 0.7823 | 0.7843 | 0.7745 |
| 0.0041 | 26.8 | 67 | 1.7925 | 0.7647 | 0.7593 | 0.7647 | 0.7567 |
| 0.0041 | 28.0 | 70 | 1.7721 | 0.7843 | 0.7823 | 0.7843 | 0.7745 |
| 0.0041 | 28.8 | 72 | 1.7919 | 0.7647 | 0.7624 | 0.7647 | 0.7510 |
| 0.0041 | 30.0 | 75 | 1.9588 | 0.7451 | 0.7521 | 0.7451 | 0.7179 |
| 0.0041 | 30.8 | 77 | 1.9200 | 0.7451 | 0.7521 | 0.7451 | 0.7179 |
| 0.0041 | 32.0 | 80 | 1.7746 | 0.7451 | 0.7521 | 0.7451 | 0.7179 |
| 0.0041 | 32.8 | 82 | 1.7253 | 0.7647 | 0.7624 | 0.7647 | 0.7510 |
| 0.0041 | 34.0 | 85 | 1.6992 | 0.7451 | 0.7382 | 0.7451 | 0.7335 |
| 0.0041 | 34.8 | 87 | 1.6938 | 0.7451 | 0.7382 | 0.7451 | 0.7335 |
| 0.0031 | 36.0 | 90 | 1.7014 | 0.7451 | 0.7382 | 0.7451 | 0.7335 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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