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segformer-b2-finetuned-segments-pv_v1_normalized_p100_4batch

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metadata
license: other
base_model: nvidia/segformer-b2-finetuned-ade-512-512
tags:
  - vision
  - image-segmentation
  - generated_from_trainer
metrics:
  - precision
model-index:
  - name: segformer-b2-finetuned-segments-pv_v1_normalized_p100_4batch
    results: []

Visualize in Weights & Biases

segformer-b2-finetuned-segments-pv_v1_normalized_p100_4batch

This model is a fine-tuned version of nvidia/segformer-b2-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
  • lr_scheduler_warmup_ratio: 0.001
  • num_epochs: 40
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Mean Iou Precision
0.01 0.9989 229 0.0088 0.8105 0.8817
0.0062 1.9978 458 0.0075 0.8201 0.8726
0.0049 2.9967 687 0.0063 0.8297 0.8867
0.0053 4.0 917 0.0055 0.8425 0.8845
0.0037 4.9989 1146 0.0058 0.8380 0.8823
0.0039 5.9978 1375 0.0211 0.6114 0.9766
0.0037 6.9967 1604 0.3403 0.0 1.0
0.0002 8.0 1834 nan 0.0 1.0
0.0003 8.9989 2063 nan 0.0 1.0
0.0864 9.9978 2292 nan 0.0 1.0
0.0035 10.9967 2521 nan 0.0 1.0
0.0045 12.0 2751 nan 0.0 1.0
0.0039 12.9989 2980 nan 0.0 1.0
0.8023 13.9978 3209 nan 0.0 1.0
0.0041 14.9967 3438 nan 0.0 1.0
7.0711 16.0 3668 nan 0.0 1.0
0.0039 16.9989 3897 nan 0.0 1.0
19.4385 17.9978 4126 nan 0.0 1.0
0.0001 18.9967 4355 nan 0.0 1.0
1.7398 20.0 4585 nan 0.0 1.0
0.2879 20.9989 4814 nan 0.0 1.0
0.0005 21.9978 5043 nan 0.0 1.0
5.8398 22.9967 5272 nan 0.0 1.0
0.0004 24.0 5502 nan 0.0 1.0
0.0002 24.9989 5731 nan 0.0 1.0
0.0016 25.9978 5960 nan 0.0 1.0
0.0034 26.9967 6189 nan 0.0 1.0
0.0004 28.0 6419 nan 0.0 1.0
0.0036 28.9989 6648 nan 0.0 1.0
0.0314 29.9978 6877 nan 0.0 1.0
0.0921 30.9967 7106 nan 0.0 1.0
89.1025 32.0 7336 nan 0.0 1.0
0.0073 32.9989 7565 nan 0.0 1.0
0.0126 33.9978 7794 nan 0.0 1.0
0.0094 34.9967 8023 nan 0.0 1.0
0.0001 36.0 8253 nan 0.0 1.0
4.3987 36.9989 8482 nan 0.0 1.0
0.0005 37.9978 8711 nan 0.0 1.0
0.0202 38.9967 8940 nan 0.0 1.0
0.1612 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