| | --- |
| | license: apache-2.0 |
| | base_model: microsoft/beit-base-patch16-224-pt22k-ft22k |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - accuracy |
| | model-index: |
| | - name: Paper_compared-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. --> |
| |
|
| | # Paper_compared-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: 0.5363 |
| | - Accuracy: 0.8409 |
| | |
| | ## 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: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | | 1.6803 | 0.9492 | 14 | 0.9171 | 0.7156 | |
| | | 0.8219 | 1.9661 | 29 | 0.5230 | 0.8330 | |
| | | 0.2323 | 2.9831 | 44 | 0.5110 | 0.8047 | |
| | | 0.1112 | 4.0 | 59 | 0.4968 | 0.8138 | |
| | | 0.0387 | 4.9492 | 73 | 0.5502 | 0.8093 | |
| | | 0.0232 | 5.9661 | 88 | 0.5506 | 0.8296 | |
| | | 0.0096 | 6.9831 | 103 | 0.5341 | 0.8431 | |
| | | 0.0068 | 8.0 | 118 | 0.6003 | 0.8149 | |
| | | 0.0046 | 8.9492 | 132 | 0.5298 | 0.8409 | |
| | | 0.0051 | 9.4915 | 140 | 0.5363 | 0.8409 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.41.1 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.19.2 |
| | - Tokenizers 0.19.1 |
| | |
