| license: apache-2.0 | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - AI-Lab-Makerere/beans | |
| metrics: | |
| - accuracy | |
| base_model: microsoft/beit-base-patch16-384 | |
| model-index: | |
| - name: beit_large512_fine_tuned | |
| results: | |
| - task: | |
| type: image-classification | |
| name: Image Classification | |
| dataset: | |
| name: beans | |
| type: beans | |
| config: train | |
| split: validation | |
| args: train | |
| metrics: | |
| - type: accuracy | |
| value: 0.9924812030075187 | |
| name: Accuracy | |
| <!-- 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_large512_fine_tuned | |
| This model is a fine-tuned version of [microsoft/beit-base-patch16-384](https://huggingface.co/microsoft/beit-base-patch16-384) on the beans dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.0353 | |
| - Accuracy: 0.9925 | |
| ## 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: 16 | |
| - eval_batch_size: 16 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 4 | |
| - total_train_batch_size: 64 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_ratio: 0.1 | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| | 4.6571 | 0.98 | 16 | 0.3870 | 0.8722 | | |
| | 0.2299 | 1.97 | 32 | 0.0632 | 0.9850 | | |
| | 0.1435 | 2.95 | 48 | 0.0353 | 0.9925 | | |
| ### Framework versions | |
| - Transformers 4.31.0 | |
| - Pytorch 2.0.1+cpu | |
| - Datasets 2.13.1 | |
| - Tokenizers 0.13.3 | |