End of training

README.md

@@ -1,199 +1,105 @@
 ---
-library_name: transformers
-tags: []
+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_segment_pv_p100_4batch
+  results: []
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
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-
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-## Model Details
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-### Model Description
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-<!-- Provide a longer summary of what this model is. -->
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-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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+<!-- 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/segformer-pv-4batches/runs/a86baba8)
+# segformer_b2_finetuned_segment_pv_p100_4batch
+
+This model is a fine-tuned version of [nvidia/segformer-b2-finetuned-ade-512-512](https://huggingface.co/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: 0.0090
+- Mean Iou: 0.8765
+- Precision: 0.9192
+
+## 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: 4e-05
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 40
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Mean Iou | Precision |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|
+| 0.5015        | 1.0   | 917   | 0.1494          | 0.5660   | 0.6026    |
+| 0.0714        | 2.0   | 1834  | 0.0237          | 0.7528   | 0.7988    |
+| 0.0171        | 3.0   | 2751  | 0.0101          | 0.7978   | 0.8930    |
+| 0.0087        | 4.0   | 3668  | 0.0072          | 0.8260   | 0.8534    |
+| 0.0058        | 5.0   | 4585  | 0.0067          | 0.8418   | 0.8981    |
+| 0.0046        | 6.0   | 5502  | 0.0056          | 0.8457   | 0.8971    |
+| 0.0038        | 7.0   | 6419  | 0.0056          | 0.8530   | 0.8770    |
+| 0.0034        | 8.0   | 7336  | 0.0056          | 0.8525   | 0.8978    |
+| 0.003         | 9.0   | 8253  | 0.0052          | 0.8643   | 0.9063    |
+| 0.0028        | 10.0  | 9170  | 0.0054          | 0.8641   | 0.9010    |
+| 0.0027        | 11.0  | 10087 | 0.0065          | 0.8489   | 0.9236    |
+| 0.0025        | 12.0  | 11004 | 0.0066          | 0.8432   | 0.9006    |
+| 0.0024        | 13.0  | 11921 | 0.0055          | 0.8637   | 0.9242    |
+| 0.0022        | 14.0  | 12838 | 0.0054          | 0.8679   | 0.9104    |
+| 0.0024        | 15.0  | 13755 | 0.0055          | 0.8719   | 0.9171    |
+| 0.0019        | 16.0  | 14672 | 0.0055          | 0.8746   | 0.9219    |
+| 0.0019        | 17.0  | 15589 | 0.0056          | 0.8668   | 0.9062    |
+| 0.0018        | 18.0  | 16506 | 0.0063          | 0.8703   | 0.9121    |
+| 0.0017        | 19.0  | 17423 | 0.0062          | 0.8694   | 0.9084    |
+| 0.0016        | 20.0  | 18340 | 0.0063          | 0.8719   | 0.9133    |
+| 0.0015        | 21.0  | 19257 | 0.0065          | 0.8734   | 0.9159    |
+| 0.0014        | 22.0  | 20174 | 0.0068          | 0.8730   | 0.9155    |
+| 0.0015        | 23.0  | 21091 | 0.0069          | 0.8719   | 0.9228    |
+| 0.0013        | 24.0  | 22008 | 0.0069          | 0.8745   | 0.9162    |
+| 0.0013        | 25.0  | 22925 | 0.0069          | 0.8757   | 0.9196    |
+| 0.0012        | 26.0  | 23842 | 0.0075          | 0.8747   | 0.9138    |
+| 0.0012        | 27.0  | 24759 | 0.0074          | 0.8750   | 0.9159    |
+| 0.0012        | 28.0  | 25676 | 0.0074          | 0.8755   | 0.9213    |
+| 0.0011        | 29.0  | 26593 | 0.0081          | 0.8762   | 0.9154    |
+| 0.0011        | 30.0  | 27510 | 0.0083          | 0.8754   | 0.9162    |
+| 0.0011        | 31.0  | 28427 | 0.0084          | 0.8753   | 0.9168    |
+| 0.001         | 32.0  | 29344 | 0.0083          | 0.8754   | 0.9202    |
+| 0.001         | 33.0  | 30261 | 0.0085          | 0.8758   | 0.9174    |
+| 0.001         | 34.0  | 31178 | 0.0085          | 0.8758   | 0.9208    |
+| 0.0009        | 35.0  | 32095 | 0.0088          | 0.8763   | 0.9191    |
+| 0.0009        | 36.0  | 33012 | 0.0090          | 0.8756   | 0.9172    |
+| 0.0009        | 37.0  | 33929 | 0.0090          | 0.8760   | 0.9181    |
+| 0.0009        | 38.0  | 34846 | 0.0087          | 0.8764   | 0.9195    |
+| 0.0009        | 39.0  | 35763 | 0.0090          | 0.8763   | 0.9184    |
+| 0.0009        | 40.0  | 36680 | 0.0090          | 0.8765   | 0.9192    |
+
+
+### 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-b2-finetuned-ade-512-512",
+  "architectures": [
+    "SegformerForSemanticSegmentation"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "decoder_hidden_size": 768,
+  "depths": [
+    3,
+    4,
+    6,
+    3
+  ],
+  "downsampling_rates": [
+    1,
+    4,
+    8,
+    16
+  ],
+  "drop_path_rate": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_sizes": [
+    64,
+    128,
+    320,
+    512
+  ],
+  "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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runs/Aug01_03-05-39_d341e027d780/events.out.tfevents.1722481561.d341e027d780.23.0

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training_args.bin

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