End of training

README.md

@@ -1,199 +1,107 @@
 ---
-library_name: transformers
-tags: []
+license: other
+base_model: nvidia/segformer-b0-finetuned-ade-512-512
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+metrics:
+- precision
+model-index:
+- name: segformer-b0-finetuned-segments-pv_v1_3x_normalized_p100_4batch
+ results: []
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
-
-### Model Description
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-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
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-## Uses
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-## How to Get Started with the Model
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-## Training Details
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-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<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)
+# segformer-b0-finetuned-segments-pv_v1_3x_normalized_p100_4batch
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.0067
+- Mean Iou: 0.8641
+- Precision: 0.9173
+
+## 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 |
+|:-------------:|:-------:|:-----:|:---------------:|:--------:|:---------:|
+| 0.0077 | 0.9993 | 687 | 0.0077 | 0.7897 | 0.8235 |
+| 0.0056 | 2.0 | 1375 | 0.0059 | 0.8193 | 0.8760 |
+| 0.0065 | 2.9993 | 2062 | 0.0064 | 0.8222 | 0.9068 |
+| 0.0047 | 4.0 | 2750 | 0.0061 | 0.8195 | 0.9299 |
+| 0.0039 | 4.9993 | 3437 | 0.0055 | 0.8440 | 0.9075 |
+| 0.0044 | 6.0 | 4125 | 0.0063 | 0.8208 | 0.8479 |
+| 0.0034 | 6.9993 | 4812 | 0.0080 | 0.7750 | 0.8153 |
+| 0.0037 | 8.0 | 5500 | 0.0053 | 0.8475 | 0.9084 |
+| 0.004 | 8.9993 | 6187 | 0.0073 | 0.8013 | 0.8237 |
+| 0.003 | 10.0 | 6875 | 0.0056 | 0.8476 | 0.8955 |
+| 0.0038 | 10.9993 | 7562 | 0.0058 | 0.8273 | 0.9144 |
+| 0.0028 | 12.0 | 8250 | 0.0065 | 0.8143 | 0.8888 |
+| 0.0031 | 12.9993 | 8937 | 0.0064 | 0.8175 | 0.9188 |
+| 0.003 | 14.0 | 9625 | 0.0051 | 0.8491 | 0.9027 |
+| 0.0025 | 14.9993 | 10312 | 0.0059 | 0.8558 | 0.9085 |
+| 0.0029 | 16.0 | 11000 | 0.0057 | 0.8454 | 0.9029 |
+| 0.0026 | 16.9993 | 11687 | 0.0057 | 0.8547 | 0.9230 |
+| 0.0024 | 18.0 | 12375 | 0.0059 | 0.8579 | 0.9045 |
+| 0.0025 | 18.9993 | 13062 | 0.0059 | 0.8645 | 0.9094 |
+| 0.0025 | 20.0 | 13750 | 0.0059 | 0.8498 | 0.9174 |
+| 0.0024 | 20.9993 | 14437 | 0.0056 | 0.8576 | 0.8970 |
+| 0.0022 | 22.0 | 15125 | 0.0063 | 0.8541 | 0.8952 |
+| 0.0031 | 22.9993 | 15812 | 0.0054 | 0.8508 | 0.9154 |
+| 0.0021 | 24.0 | 16500 | 0.0057 | 0.8545 | 0.9119 |
+| 0.0022 | 24.9993 | 17187 | 0.0058 | 0.8474 | 0.9149 |
+| 0.0022 | 26.0 | 17875 | 0.0066 | 0.8325 | 0.8879 |
+| 0.0021 | 26.9993 | 18562 | 0.0062 | 0.8522 | 0.9156 |
+| 0.0021 | 28.0 | 19250 | 0.0063 | 0.8488 | 0.8932 |
+| 0.002 | 28.9993 | 19937 | 0.0061 | 0.8579 | 0.9200 |
+| 0.002 | 30.0 | 20625 | 0.0059 | 0.8624 | 0.9182 |
+| 0.0021 | 30.9993 | 21312 | 0.0061 | 0.8564 | 0.9013 |
+| 0.0019 | 32.0 | 22000 | 0.0060 | 0.8601 | 0.9091 |
+| 0.0018 | 32.9993 | 22687 | 0.0059 | 0.8640 | 0.9163 |
+| 0.0017 | 34.0 | 23375 | 0.0062 | 0.8622 | 0.9187 |
+| 0.0017 | 34.9993 | 24062 | 0.0062 | 0.8634 | 0.9245 |
+| 0.0017 | 36.0 | 24750 | 0.0064 | 0.8655 | 0.9196 |
+| 0.0017 | 36.9993 | 25437 | 0.0063 | 0.8642 | 0.9197 |
+| 0.0016 | 38.0 | 26125 | 0.0065 | 0.8634 | 0.9166 |
+| 0.0016 | 38.9993 | 26812 | 0.0067 | 0.8639 | 0.9186 |
+| 0.0016 | 39.9709 | 27480 | 0.0067 | 0.8641 | 0.9173 |
+
+
+### Framework versions
+
+- Transformers 4.42.3
+- Pytorch 2.1.2
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

@@ -0,0 +1,78 @@
+{
+ "_name_or_path": "nvidia/segformer-b0-finetuned-ade-512-512",
+ "architectures": [
+ "SegformerForSemanticSegmentation"
+ ],
+ "attention_probs_dropout_prob": 0.0,
+ "classifier_dropout_prob": 0.1,
+ "decoder_hidden_size": 256,
+ "depths": [
+ 2,
+ 2,
+ 2,
+ 2
+ ],
+ "downsampling_rates": [
+ 1,
+ 4,
+ 8,
+ 16
+ ],
+ "drop_path_rate": 0.1,
+ "hidden_act": "gelu",
+ "hidden_dropout_prob": 0.0,
+ "hidden_sizes": [
+ 32,
+ 64,
+ 160,
+ 256
+ ],
+ "id2label": {
+ "0": "unlabeled",
+ "1": "PV"
+ },
+ "image_size": 224,
+ "initializer_range": 0.02,
+ "label2id": {
+ "PV": 1,
+ "unlabeled": 0
+ },
+ "layer_norm_eps": 1e-06,
+ "mlp_ratios": [
+ 4,
+ 4,
+ 4,
+ 4
+ ],
+ "model_type": "segformer",
+ "num_attention_heads": [
+ 1,
+ 2,
+ 5,
+ 8
+ ],
+ "num_channels": 3,
+ "num_encoder_blocks": 4,
+ "patch_sizes": [
+ 7,
+ 3,
+ 3,
+ 3
+ ],
+ "reshape_last_stage": true,
+ "semantic_loss_ignore_index": 255,
+ "sr_ratios": [
+ 8,
+ 4,
+ 2,
+ 1
+ ],
+ "strides": [
+ 4,
+ 2,
+ 2,
+ 2
+ ],
+ "torch_dtype": "float32",
+ "transformers_version": "4.42.3"
+}

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