This model is a fine-tuned version of nvidia/mit-b0 on the julia-wenkmann/TennisSegmentation dataset.
It achieves the following results on the evaluation set:
eval_loss: 0.0158
eval_mean_iou: 0.4994
eval_mean_accuracy: 0.6483
eval_overall_accuracy: 0.9915
eval_accuracy_undefined: nan
eval_accuracy_object: nan
eval_accuracy_ball: 0.0
eval_accuracy_playerTop: 0.7071
eval_accuracy_playerBottom: 0.8904
eval_accuracy_court: 0.9956
eval_iou_undefined: 0.0
eval_iou_object: nan
eval_iou_ball: 0.0
eval_iou_playerTop: 0.7071
eval_iou_playerBottom: 0.7968
eval_iou_court: 0.9931
eval_runtime: 8.2745
eval_samples_per_second: 2.175
eval_steps_per_second: 1.088
epoch: 29.41
step: 1000
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
