metadata

license: other
base_model: nvidia/mit-b0
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
model-index:
  - name: segformer-b0-finetuned-v0
    results: []

segformer-b0-finetuned-v0

This model is a fine-tuned version of nvidia/mit-b0 on the tontokoton/artery-ultrasound-siit dataset. It achieves the following results on the evaluation set:

eval_loss: 1.4971
eval_mean_iou: 0.1068
eval_mean_accuracy: 0.2327
eval_overall_accuracy: 0.8437
eval_accuracy_artery: nan
eval_accuracy_vein: 0.0062
eval_accuracy_nerve: 0.0022
eval_accuracy_muscle1: 0.0
eval_accuracy_muscle2: 0.9224
eval_accuracy_muscle3: nan
eval_accuracy_muscle4: nan
eval_accuracy_unknown: nan
eval_iou_artery: 0.0
eval_iou_vein: 0.0061
eval_iou_nerve: 0.0021
eval_iou_muscle1: 0.0
eval_iou_muscle2: 0.8458
eval_iou_muscle3: 0.0
eval_iou_muscle4: 0.0
eval_iou_unknown: 0.0
eval_runtime: 11.3293
eval_samples_per_second: 1.765
eval_steps_per_second: 0.883
epoch: 2.25
step: 90

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: 1e-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 4.34.0
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.14.1