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