segformer-custom
This model is a fine-tuned version of sanjaybora04/segformer-custom on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.4589
- eval_mean_iou: 0.6566
- eval_mean_accuracy: 0.7804
- eval_iou_background: 0.8221
- eval_iou_wall: 0.7010
- eval_iou_floor: 0.7254
- eval_iou_ceiling: 0.7398
- eval_iou_stairs: 0.3269
- eval_iou_countertop: 0.6245
- eval_accuracy_background: 0.9023
- eval_accuracy_wall: 0.8342
- eval_accuracy_floor: 0.8285
- eval_accuracy_ceiling: 0.8565
- eval_accuracy_stairs: 0.3478
- eval_accuracy_countertop: 0.9131
- eval_runtime: 13.9462
- eval_samples_per_second: 10.756
- eval_steps_per_second: 1.076
- epoch: 5.0
- step: 6250
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: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 3.6.0
- Tokenizers 0.22.2
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