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--- |
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license: other |
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base_model: nvidia/segformer-b1-finetuned-ade-512-512 |
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tags: |
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- vision |
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- image-segmentation |
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- generated_from_trainer |
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metrics: |
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- precision |
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model-index: |
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- name: segformer-b1-finetuned-segments-pv_v1_3x_normalized_p100_4batch |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mouadn773/huggingface/runs/ydmwnhgs) |
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# segformer-b1-finetuned-segments-pv_v1_3x_normalized_p100_4batch |
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This model is a fine-tuned version of [nvidia/segformer-b1-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b1-finetuned-ade-512-512) on the mouadenna/satellite_PV_dataset_train_test_v1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0087 |
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- Mean Iou: 0.8602 |
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- Precision: 0.9152 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0004 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.001 |
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- num_epochs: 40 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Precision | |
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|:-------------:|:-------:|:-----:|:---------------:|:--------:|:---------:| |
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| 0.0073 | 0.9993 | 687 | 0.0072 | 0.7997 | 0.8395 | |
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| 0.0052 | 2.0 | 1375 | 0.0069 | 0.8039 | 0.8906 | |
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| 0.0051 | 2.9993 | 2062 | 0.0060 | 0.8301 | 0.8951 | |
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| 0.0048 | 4.0 | 2750 | 0.0057 | 0.8223 | 0.9070 | |
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| 0.0039 | 4.9993 | 3437 | 0.0054 | 0.8433 | 0.9104 | |
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| 0.0042 | 6.0 | 4125 | 0.0054 | 0.8414 | 0.8779 | |
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| 0.0031 | 6.9993 | 4812 | 0.0052 | 0.8453 | 0.8852 | |
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| 0.0034 | 8.0 | 5500 | 0.0051 | 0.8526 | 0.9146 | |
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| 0.0036 | 8.9993 | 6187 | 0.0059 | 0.8319 | 0.8884 | |
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| 0.0027 | 10.0 | 6875 | 0.0058 | 0.8453 | 0.8990 | |
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| 0.0028 | 10.9993 | 7562 | 0.0052 | 0.8552 | 0.9152 | |
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| 0.0027 | 12.0 | 8250 | 0.0062 | 0.8459 | 0.9038 | |
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| 0.0032 | 12.9993 | 8937 | 0.0056 | 0.8506 | 0.9163 | |
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| 0.0024 | 14.0 | 9625 | 0.0062 | 0.8529 | 0.9189 | |
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| 0.0035 | 14.9993 | 10312 | 0.0058 | 0.8464 | 0.9102 | |
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| 0.0024 | 16.0 | 11000 | 0.0059 | 0.8575 | 0.9126 | |
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| 0.0023 | 16.9993 | 11687 | 0.0057 | 0.8527 | 0.9201 | |
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| 0.0024 | 18.0 | 12375 | 0.0060 | 0.8573 | 0.9177 | |
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| 0.0028 | 18.9993 | 13062 | 0.0063 | 0.8601 | 0.9064 | |
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| 0.0023 | 20.0 | 13750 | 0.0061 | 0.8589 | 0.9164 | |
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| 0.002 | 20.9993 | 14437 | 0.0061 | 0.8611 | 0.9046 | |
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| 0.002 | 22.0 | 15125 | 0.0057 | 0.8633 | 0.9143 | |
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| 0.002 | 22.9993 | 15812 | 0.0067 | 0.8552 | 0.9133 | |
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| 0.0018 | 24.0 | 16500 | 0.0068 | 0.8594 | 0.9174 | |
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| 0.0021 | 24.9993 | 17187 | 0.0063 | 0.8545 | 0.9111 | |
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| 0.0023 | 26.0 | 17875 | 0.0055 | 0.8642 | 0.9149 | |
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| 0.0019 | 26.9993 | 18562 | 0.0060 | 0.8627 | 0.9152 | |
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| 0.0017 | 28.0 | 19250 | 0.0063 | 0.8658 | 0.9148 | |
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| 0.0017 | 28.9993 | 19937 | 0.0067 | 0.8644 | 0.9085 | |
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| 0.0017 | 30.0 | 20625 | 0.0068 | 0.8578 | 0.9110 | |
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| 0.0017 | 30.9993 | 21312 | 0.0067 | 0.8585 | 0.9130 | |
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| 0.0015 | 32.0 | 22000 | 0.0069 | 0.8613 | 0.9103 | |
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| 0.0015 | 32.9993 | 22687 | 0.0073 | 0.8599 | 0.9200 | |
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| 0.0014 | 34.0 | 23375 | 0.0074 | 0.8605 | 0.9181 | |
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| 0.0014 | 34.9993 | 24062 | 0.0079 | 0.8581 | 0.9174 | |
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| 0.0013 | 36.0 | 24750 | 0.0081 | 0.8582 | 0.9123 | |
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| 0.0013 | 36.9993 | 25437 | 0.0084 | 0.8599 | 0.9166 | |
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| 0.0012 | 38.0 | 26125 | 0.0084 | 0.8603 | 0.9139 | |
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| 0.0013 | 38.9993 | 26812 | 0.0092 | 0.8599 | 0.9193 | |
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| 0.0012 | 39.9709 | 27480 | 0.0087 | 0.8602 | 0.9152 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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