| license: other | |
| tags: | |
| - generated_from_trainer | |
| datasets: | |
| - imagefolder | |
| metrics: | |
| - accuracy | |
| base_model: nvidia/mit-b0 | |
| model-index: | |
| - name: histo_train_segformer | |
| results: | |
| - task: | |
| type: image-classification | |
| name: Image Classification | |
| dataset: | |
| name: imagefolder | |
| type: imagefolder | |
| config: default | |
| split: train | |
| args: default | |
| metrics: | |
| - type: accuracy | |
| value: 0.875 | |
| 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. --> | |
| # histo_train_segformer | |
| This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the imagefolder dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.3830 | |
| - Accuracy: 0.875 | |
| ## 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: 0.0002 | |
| - train_batch_size: 64 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 20 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| | |
| | 0.2234 | 16.67 | 100 | 0.3830 | 0.875 | | |
| ### Framework versions | |
| - Transformers 4.27.3 | |
| - Pytorch 1.13.1+cu116 | |
| - Datasets 2.10.1 | |
| - Tokenizers 0.13.2 | |