segformer-b5-finetuned-ce-head-batch4
This model is a fine-tuned version of nvidia/mit-b5 on the None dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.0871
- eval_mean_iou: 0.7378
- eval_mean_accuracy: 0.8916
- eval_overall_accuracy: 0.9634
- eval_accuracy_bg: 0.9710
- eval_accuracy_head: 0.8121
- eval_iou_bg: 0.9620
- eval_iou_head: 0.5136
- eval_runtime: 3.4796
- eval_samples_per_second: 5.173
- eval_steps_per_second: 2.586
- epoch: 5.9706
- step: 203
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: 7e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use OptimizerNames.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: 30
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.3
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Base model
nvidia/mit-b5