metadata

license: other
base_model: nvidia/mit-b5
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
model-index:
  - name: segformer-b5-miic-tl
    results: []

segformer-b5-miic-tl

This model is a fine-tuned version of nvidia/mit-b5 on the yijisuk/ic-chip-sample dataset. It achieves the following results on the evaluation set:

eval_loss: 0.2028
eval_mean_iou: 0.3885
eval_mean_accuracy: 0.7770
eval_overall_accuracy: 0.7770
eval_accuracy_unlabeled: nan
eval_accuracy_circuit: 0.7770
eval_iou_unlabeled: 0.0
eval_iou_circuit: 0.7770
eval_dice_coefficient: 0.7854
eval_runtime: 1.8601
eval_samples_per_second: 5.376
eval_steps_per_second: 2.688
epoch: 48.75
step: 3900

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
lr_scheduler_type: linear
num_epochs: 50

Framework versions

Transformers 4.36.2
Pytorch 1.11.0+cu115
Datasets 2.15.0
Tokenizers 0.15.0