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--- |
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license: other |
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base_model: nvidia/segformer-b0-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-b0-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/yy31wgdz) |
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# segformer-b0-finetuned-segments-pv_v1_3x_normalized_p100_4batch |
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This model is a fine-tuned version of [nvidia/segformer-b0-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b0-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: 0.0067 |
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- Mean Iou: 0.8641 |
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- Precision: 0.9173 |
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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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| 0.0077 | 0.9993 | 687 | 0.0077 | 0.7897 | 0.8235 | |
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| 0.0056 | 2.0 | 1375 | 0.0059 | 0.8193 | 0.8760 | |
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| 0.0065 | 2.9993 | 2062 | 0.0064 | 0.8222 | 0.9068 | |
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| 0.0047 | 4.0 | 2750 | 0.0061 | 0.8195 | 0.9299 | |
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| 0.0039 | 4.9993 | 3437 | 0.0055 | 0.8440 | 0.9075 | |
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| 0.0044 | 6.0 | 4125 | 0.0063 | 0.8208 | 0.8479 | |
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| 0.0034 | 6.9993 | 4812 | 0.0080 | 0.7750 | 0.8153 | |
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| 0.0037 | 8.0 | 5500 | 0.0053 | 0.8475 | 0.9084 | |
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| 0.004 | 8.9993 | 6187 | 0.0073 | 0.8013 | 0.8237 | |
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| 0.003 | 10.0 | 6875 | 0.0056 | 0.8476 | 0.8955 | |
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| 0.0038 | 10.9993 | 7562 | 0.0058 | 0.8273 | 0.9144 | |
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| 0.0028 | 12.0 | 8250 | 0.0065 | 0.8143 | 0.8888 | |
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| 0.0031 | 12.9993 | 8937 | 0.0064 | 0.8175 | 0.9188 | |
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| 0.003 | 14.0 | 9625 | 0.0051 | 0.8491 | 0.9027 | |
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| 0.0025 | 14.9993 | 10312 | 0.0059 | 0.8558 | 0.9085 | |
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| 0.0029 | 16.0 | 11000 | 0.0057 | 0.8454 | 0.9029 | |
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| 0.0026 | 16.9993 | 11687 | 0.0057 | 0.8547 | 0.9230 | |
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| 0.0024 | 18.0 | 12375 | 0.0059 | 0.8579 | 0.9045 | |
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| 0.0025 | 18.9993 | 13062 | 0.0059 | 0.8645 | 0.9094 | |
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| 0.0025 | 20.0 | 13750 | 0.0059 | 0.8498 | 0.9174 | |
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| 0.0024 | 20.9993 | 14437 | 0.0056 | 0.8576 | 0.8970 | |
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| 0.0022 | 22.0 | 15125 | 0.0063 | 0.8541 | 0.8952 | |
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| 0.0031 | 22.9993 | 15812 | 0.0054 | 0.8508 | 0.9154 | |
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| 0.0021 | 24.0 | 16500 | 0.0057 | 0.8545 | 0.9119 | |
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| 0.0022 | 24.9993 | 17187 | 0.0058 | 0.8474 | 0.9149 | |
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| 0.0022 | 26.0 | 17875 | 0.0066 | 0.8325 | 0.8879 | |
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| 0.0021 | 26.9993 | 18562 | 0.0062 | 0.8522 | 0.9156 | |
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| 0.0021 | 28.0 | 19250 | 0.0063 | 0.8488 | 0.8932 | |
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| 0.002 | 28.9993 | 19937 | 0.0061 | 0.8579 | 0.9200 | |
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| 0.002 | 30.0 | 20625 | 0.0059 | 0.8624 | 0.9182 | |
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| 0.0021 | 30.9993 | 21312 | 0.0061 | 0.8564 | 0.9013 | |
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| 0.0019 | 32.0 | 22000 | 0.0060 | 0.8601 | 0.9091 | |
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| 0.0018 | 32.9993 | 22687 | 0.0059 | 0.8640 | 0.9163 | |
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| 0.0017 | 34.0 | 23375 | 0.0062 | 0.8622 | 0.9187 | |
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| 0.0017 | 34.9993 | 24062 | 0.0062 | 0.8634 | 0.9245 | |
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| 0.0017 | 36.0 | 24750 | 0.0064 | 0.8655 | 0.9196 | |
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| 0.0017 | 36.9993 | 25437 | 0.0063 | 0.8642 | 0.9197 | |
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| 0.0016 | 38.0 | 26125 | 0.0065 | 0.8634 | 0.9166 | |
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| 0.0016 | 38.9993 | 26812 | 0.0067 | 0.8639 | 0.9186 | |
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| 0.0016 | 39.9709 | 27480 | 0.0067 | 0.8641 | 0.9173 | |
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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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