segformer-b01-finetuned-wrinkle
This model is a fine-tuned version of nvidia/mit-b1 on the face-wrinkles dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.0002
- eval_mean_iou: 0.0
- eval_mean_accuracy: nan
- eval_overall_accuracy: nan
- eval_accuracy_unlabeled: nan
- eval_accuracy_wrinkle: nan
- eval_iou_unlabeled: 0.0
- eval_iou_wrinkle: 0.0
- eval_runtime: 13.0305
- eval_samples_per_second: 10.053
- eval_steps_per_second: 5.065
- epoch: 2.3978
- step: 880
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
nvidia/mit-b1