| --- |
| license: apache-2.0 |
| base_model: microsoft/beit-base-patch16-224-pt22k-ft22k |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: 0.50-800Train-100Test-beit-base |
| 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. --> |
|
|
| # 0.50-800Train-100Test-beit-base |
|
|
| This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7501 |
| - Accuracy: 0.8192 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## 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: 16 |
| - total_train_batch_size: 512 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | 0.7627 | 0.9536 | 18 | 0.6991 | 0.7860 | |
| | 0.3414 | 1.9603 | 37 | 0.5881 | 0.8070 | |
| | 0.1402 | 2.9669 | 56 | 0.5879 | 0.8114 | |
| | 0.0663 | 3.9735 | 75 | 0.6249 | 0.8175 | |
| | 0.0377 | 4.9801 | 94 | 0.6539 | 0.8210 | |
| | 0.0314 | 5.9868 | 113 | 0.7074 | 0.8175 | |
| | 0.0189 | 6.9934 | 132 | 0.7596 | 0.8210 | |
| | 0.0147 | 8.0 | 151 | 0.7211 | 0.8253 | |
| | 0.0157 | 8.9536 | 169 | 0.7412 | 0.8166 | |
| | 0.0095 | 9.5364 | 180 | 0.7501 | 0.8192 | |
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| ### Framework versions |
|
|
| - Transformers 4.41.2 |
| - Pytorch 2.1.2 |
| - Datasets 2.19.2 |
| - Tokenizers 0.19.1 |
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|
