--- license: other base_model: nvidia/segformer-b0-finetuned-ade-512-512 tags: - generated_from_trainer datasets: - imagefolder metrics: - accuracy model-index: - name: segformer-original-5 results: - task: name: Image Classification type: image-classification dataset: name: imagefolder type: imagefolder config: default split: train args: default metrics: - name: Accuracy type: accuracy value: 0.718299164768413 --- # segformer-original-5 This model is a fine-tuned version of [nvidia/segformer-b0-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b0-finetuned-ade-512-512) on the imagefolder dataset. It achieves the following results on the evaluation set: - Loss: 1.8862 - Accuracy: 0.7183 ## 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: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 5.8809 | 1.0 | 247 | 4.9508 | 0.0716 | | 4.6081 | 2.0 | 494 | 3.3703 | 0.3551 | | 3.4538 | 3.0 | 741 | 2.5005 | 0.5662 | | 3.0418 | 4.0 | 988 | 2.0606 | 0.6778 | | 2.7046 | 5.0 | 1235 | 1.8862 | 0.7183 | ### Framework versions - Transformers 4.39.3 - Pytorch 2.2.2+cu121 - Datasets 3.0.0 - Tokenizers 0.15.2