| --- |
| 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 | |
|
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|
| ### Framework versions |
|
|
| - Transformers 4.40.1 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
|
|
