NICOPOI-9
/

segformer-b0-finetuned-morphpadver1-no_ckp-3

@@ -1,199 +1,81 @@
----
-library_name: transformers
-tags: []
----
-# Model Card for Model ID
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-## Model Details
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+---
+library_name: transformers
+license: other
+base_model: nvidia/mit-b0
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b0-finetuned-morphpadver1-no_ckp-3
+  results: []
+---
+<!-- 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. -->
+# segformer-b0-finetuned-morphpadver1-no_ckp-3
+This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the NICOPOI-9/morphpad_512_4class dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0023
+- Mean Iou: 0.9987
+- Mean Accuracy: 0.9993
+- Overall Accuracy: 0.9994
+- Accuracy 0-0: 0.9991
+- Accuracy 0-90: 0.9992
+- Accuracy 90-0: 0.9993
+- Accuracy 90-90: 0.9998
+- Iou 0-0: 0.9990
+- Iou 0-90: 0.9984
+- Iou 90-0: 0.9984
+- Iou 90-90: 0.9990
+## 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: 6e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 5
+### Training results
+| Training Loss | Epoch  | Step  | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy 0-0 | Accuracy 0-90 | Accuracy 90-0 | Accuracy 90-90 | Iou 0-0 | Iou 0-90 | Iou 90-0 | Iou 90-90 |
+|:-------------:|:------:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:-------------:|:-------------:|:--------------:|:-------:|:--------:|:--------:|:---------:|
+| 0.0554        | 0.4449 | 4000  | 0.0432          | 0.9709   | 0.9852        | 0.9854           | 0.9926       | 0.9779        | 0.9811        | 0.9893         | 0.9855  | 0.9560   | 0.9565   | 0.9854    |
+| 0.0175        | 0.8898 | 8000  | 0.0254          | 0.9860   | 0.9929        | 0.9930           | 0.9962       | 0.9889        | 0.9897        | 0.9970         | 0.9934  | 0.9785   | 0.9776   | 0.9944    |
+| 0.0213        | 1.3347 | 12000 | 0.0190          | 0.9921   | 0.9961        | 0.9961           | 0.9977       | 0.9925        | 0.9962        | 0.9979         | 0.9962  | 0.9879   | 0.9879   | 0.9965    |
+| 0.0092        | 1.7796 | 16000 | 0.0148          | 0.9939   | 0.9970        | 0.9970           | 0.9986       | 0.9941        | 0.9972        | 0.9980         | 0.9973  | 0.9905   | 0.9904   | 0.9974    |
+| 0.0055        | 2.2244 | 20000 | 0.0054          | 0.9970   | 0.9985        | 0.9985           | 0.9989       | 0.9982        | 0.9976        | 0.9991         | 0.9982  | 0.9957   | 0.9957   | 0.9982    |
+| 0.004         | 2.6693 | 24000 | 0.0040          | 0.9977   | 0.9988        | 0.9988           | 0.9995       | 0.9983        | 0.9984        | 0.9991         | 0.9984  | 0.9970   | 0.9968   | 0.9985    |
+| 0.0029        | 3.1142 | 28000 | 0.0078          | 0.9973   | 0.9987        | 0.9987           | 0.9993       | 0.9968        | 0.9990        | 0.9995         | 0.9989  | 0.9958   | 0.9958   | 0.9988    |
+| 0.0125        | 3.5591 | 32000 | 0.0104          | 0.9970   | 0.9985        | 0.9985           | 0.9996       | 0.9958        | 0.9989        | 0.9996         | 0.9990  | 0.9949   | 0.9950   | 0.9989    |
+| 0.0032        | 4.0040 | 36000 | 0.0030          | 0.9982   | 0.9991        | 0.9991           | 0.9996       | 0.9979        | 0.9992        | 0.9997         | 0.9990  | 0.9974   | 0.9975   | 0.9989    |
+| 0.0051        | 4.4489 | 40000 | 0.0028          | 0.9981   | 0.9991        | 0.9991           | 0.9997       | 0.9974        | 0.9995        | 0.9997         | 0.9991  | 0.9971   | 0.9973   | 0.9990    |
+| 0.0295        | 4.8938 | 44000 | 0.0023          | 0.9987   | 0.9993        | 0.9994           | 0.9991       | 0.9992        | 0.9993        | 0.9998         | 0.9990  | 0.9984   | 0.9984   | 0.9990    |
+### Framework versions
+- Transformers 4.48.3
+- Pytorch 2.1.0
+- Datasets 3.2.0
+- Tokenizers 0.21.0

config.json ADDED Viewed

	@@ -0,0 +1,82 @@

+{
+  "_name_or_path": "nvidia/mit-b0",
+  "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": "0-0",
+    "1": "0-90",
+    "2": "90-0",
+    "3": "90-90"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "0-0": 0,
+    "0-90": 1,
+    "90-0": 2,
+    "90-90": 3
+  },
+  "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": "4.48.3"
+}

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