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segformer-b1-finetuned-segments-pv_v1_normalized_t4_16batch

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metadata
license: other
base_model: nvidia/segformer-b3-finetuned-ade-512-512
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
metrics:
  - precision
model-index:
  - name: segformer-b1-finetuned-segments-pv_v1_normalized_t4_16batch
    results: []

Visualize in Weights & Biases

segformer-b1-finetuned-segments-pv_v1_normalized_t4_16batch

This model is a fine-tuned version of nvidia/segformer-b3-finetuned-ade-512-512 on the mouadenna/satellite_PV_dataset_train_test_v1 dataset. It achieves the following results on the evaluation set:

  • Loss: nan
  • Mean Iou: 0.0
  • Precision: 1.0

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
  • num_epochs: 40
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Mean Iou Precision
0.0056 0.9989 229 0.0099 0.7568 0.7827
0.0092 1.9978 458 0.0113 0.7247 0.7360
0.0069 2.9967 687 0.0051 0.8440 0.9106
0.0159 4.0 917 0.0057 0.8317 0.8635
0.0124 4.9989 1146 0.0099 0.8223 0.9292
0.0033 5.9978 1375 0.2415 0.0 1.0
0.0 6.9967 1604 nan 0.0 1.0
0.0 8.0 1834 nan 0.0 1.0
0.0 8.9989 2063 nan 0.0 1.0
0.0 9.9978 2292 nan 0.0 1.0
0.0 10.9967 2521 nan 0.0 1.0
0.0 12.0 2751 nan 0.0 1.0
0.0 12.9989 2980 nan 0.0 1.0
0.0 13.9978 3209 nan 0.0 1.0
0.0 14.9967 3438 nan 0.0 1.0
0.0 16.0 3668 nan 0.0 1.0
0.0 16.9989 3897 nan 0.0 1.0
0.0 17.9978 4126 nan 0.0 1.0
0.0 18.9967 4355 nan 0.0 1.0
0.0 20.0 4585 nan 0.0 1.0
0.0 20.9989 4814 nan 0.0 1.0
0.0 21.9978 5043 nan 0.0 1.0
0.0 22.9967 5272 nan 0.0 1.0
0.0 24.0 5502 nan 0.0 1.0
0.0 24.9989 5731 nan 0.0 1.0
0.0 25.9978 5960 nan 0.0 1.0
0.0 26.9967 6189 nan 0.0 1.0
0.0 28.0 6419 nan 0.0 1.0
0.0 28.9989 6648 nan 0.0 1.0
0.0 29.9978 6877 nan 0.0 1.0
0.0 30.9967 7106 nan 0.0 1.0
0.0 32.0 7336 nan 0.0 1.0
0.0 32.9989 7565 nan 0.0 1.0
0.0 33.9978 7794 nan 0.0 1.0
0.0 34.9967 8023 nan 0.0 1.0
0.0 36.0 8253 nan 0.0 1.0
0.0 36.9989 8482 nan 0.0 1.0
0.0 37.9978 8711 nan 0.0 1.0
0.0 38.9967 8940 nan 0.0 1.0
0.0 39.9564 9160 nan 0.0 1.0

Framework versions

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