README.md

metadata

license: other
base_model: nvidia/segformer-b1-finetuned-ade-512-512
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
metrics:
  - precision
  - recall
model-index:
  - name: segformer-b1-finetuned-segments-pv_v1_normalized_p100_4batch_try_7_31
    results: []

segformer-b1-finetuned-segments-pv_v1_normalized_p100_4batch_try_7_31

This model is a fine-tuned version of nvidia/segformer-b1-finetuned-ade-512-512 on the mouadenna/satellite_PV_dataset_train_test_v1 dataset. It achieves the following results on the evaluation set:

• Loss: 0.0133
• Mean Iou: 0.8164
• Precision: 0.8785
• Recall: 0.9203

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: 0.0004
• train_batch_size: 4
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Mean Iou	Precision	Recall
0.0151	0.9989	229	0.0133	0.8164	0.8785	0.9203

Framework versions

• Transformers 4.42.3
• Pytorch 2.1.2
• Datasets 2.20.0
• Tokenizers 0.19.1