--- license: apache-2.0 tags: - generated_from_trainer model-index: - name: segformer-b0-finetuned-pokemon results: [] --- # segformer-b0-finetuned-pokemon This model is a fine-tuned version of [ydmeira/segformer-b0-finetuned-pokemon](https://huggingface.co/ydmeira/segformer-b0-finetuned-pokemon) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0157 - Mean Iou: 0.4970 - Mean Accuracy: 0.9940 - Overall Accuracy: 0.9940 - Per Category Iou: [0.0, 0.9940101727137823] - Per Category Accuracy: [nan, 0.9940101727137823] ## 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: 6e-05 - train_batch_size: 24 - eval_batch_size: 24 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou | Per Category Accuracy | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------------:|:-------------------------:| | 0.0175 | 45.0 | 1305 | 0.0157 | 0.4971 | 0.9943 | 0.9943 | [0.0, 0.9942906494536522] | [nan, 0.9942906494536522] | | 0.018 | 46.0 | 1334 | 0.0157 | 0.4968 | 0.9936 | 0.9936 | [0.0, 0.9936369941650801] | [nan, 0.9936369941650801] | | 0.0185 | 47.0 | 1363 | 0.0157 | 0.4971 | 0.9943 | 0.9943 | [0.0, 0.9942791789145462] | [nan, 0.9942791789145462] | | 0.018 | 48.0 | 1392 | 0.0157 | 0.4969 | 0.9937 | 0.9937 | [0.0, 0.9937245121725857] | [nan, 0.9937245121725857] | | 0.0183 | 49.0 | 1421 | 0.0157 | 0.4969 | 0.9939 | 0.9939 | [0.0, 0.9938530594161242] | [nan, 0.9938530594161242] | | 0.0196 | 50.0 | 1450 | 0.0157 | 0.4970 | 0.9940 | 0.9940 | [0.0, 0.9940101727137823] | [nan, 0.9940101727137823] | ### Framework versions - Transformers 4.20.1 - Pytorch 1.12.0+cu113 - Datasets 2.3.2 - Tokenizers 0.12.1