End of training

README.md

@@ -1,199 +1,88 @@
----
-library_name: transformers
-tags: []
----
-
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
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-### 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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-### Training Procedure
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-#### Training Hyperparameters
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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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+---
+library_name: transformers
+license: other
+base_model: nvidia/mit-b3
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b3-finetuned-morphpadver1-hgo-coord-v4
+  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-b3-finetuned-morphpadver1-hgo-coord-v4
+
+This model is a fine-tuned version of [nvidia/mit-b3](https://huggingface.co/nvidia/mit-b3) on the NICOPOI-9/morphpad_coord_hgo_512_4class_v2 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0105
+- Mean Iou: 0.9978
+- Mean Accuracy: 0.9989
+- Overall Accuracy: 0.9989
+- Accuracy 0-0: 0.9991
+- Accuracy 0-90: 0.9988
+- Accuracy 90-0: 0.9988
+- Accuracy 90-90: 0.9989
+- Iou 0-0: 0.9983
+- Iou 0-90: 0.9977
+- Iou 90-0: 0.9978
+- Iou 90-90: 0.9974
+
+## 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: 50
+
+### 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 |
+|:-------------:|:-------:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:-------------:|:-------------:|:--------------:|:-------:|:--------:|:--------:|:---------:|
+| 1.0526        | 2.6525  | 4000  | 1.0174          | 0.3366   | 0.5028        | 0.5035           | 0.5781       | 0.3249        | 0.6323        | 0.4758         | 0.3780  | 0.2714   | 0.3136   | 0.3836    |
+| 0.7543        | 5.3050  | 8000  | 0.5721          | 0.5952   | 0.7459        | 0.7458           | 0.7487       | 0.7334        | 0.6962        | 0.8051         | 0.6389  | 0.5638   | 0.5555   | 0.6227    |
+| 0.1714        | 7.9576  | 12000 | 0.1845          | 0.8808   | 0.9366        | 0.9366           | 0.9416       | 0.9454        | 0.9140        | 0.9455         | 0.8984  | 0.8681   | 0.8613   | 0.8956    |
+| 0.2092        | 10.6101 | 16000 | 0.0953          | 0.9378   | 0.9679        | 0.9679           | 0.9719       | 0.9663        | 0.9730        | 0.9602         | 0.9466  | 0.9322   | 0.9312   | 0.9412    |
+| 0.0773        | 13.2626 | 20000 | 0.1115          | 0.9348   | 0.9663        | 0.9663           | 0.9665       | 0.9728        | 0.9588        | 0.9672         | 0.9450  | 0.9220   | 0.9319   | 0.9405    |
+| 0.1           | 15.9151 | 24000 | 0.0842          | 0.9597   | 0.9794        | 0.9794           | 0.9792       | 0.9743        | 0.9802        | 0.9840         | 0.9642  | 0.9559   | 0.9539   | 0.9649    |
+| 0.0297        | 18.5676 | 28000 | 0.0524          | 0.9706   | 0.9851        | 0.9851           | 0.9855       | 0.9868        | 0.9886        | 0.9794         | 0.9753  | 0.9676   | 0.9666   | 0.9728    |
+| 0.0188        | 21.2202 | 32000 | 0.0463          | 0.9813   | 0.9906        | 0.9906           | 0.9911       | 0.9884        | 0.9899        | 0.9930         | 0.9828  | 0.9804   | 0.9787   | 0.9834    |
+| 0.0987        | 23.8727 | 36000 | 0.0377          | 0.9849   | 0.9924        | 0.9924           | 0.9913       | 0.9967        | 0.9885        | 0.9932         | 0.9866  | 0.9816   | 0.9844   | 0.9871    |
+| 0.1753        | 26.5252 | 40000 | 0.0367          | 0.9878   | 0.9939        | 0.9938           | 0.9922       | 0.9929        | 0.9947        | 0.9957         | 0.9876  | 0.9879   | 0.9853   | 0.9903    |
+| 0.0536        | 29.1777 | 44000 | 0.0392          | 0.9880   | 0.9939        | 0.9939           | 0.9946       | 0.9945        | 0.9933        | 0.9934         | 0.9891  | 0.9875   | 0.9859   | 0.9893    |
+| 0.0273        | 31.8302 | 48000 | 0.0450          | 0.9879   | 0.9939        | 0.9939           | 0.9946       | 0.9922        | 0.9937        | 0.9952         | 0.9897  | 0.9850   | 0.9872   | 0.9898    |
+| 0.006         | 34.4828 | 52000 | 0.0272          | 0.9936   | 0.9968        | 0.9968           | 0.9972       | 0.9968        | 0.9966        | 0.9965         | 0.9940  | 0.9938   | 0.9927   | 0.9937    |
+| 0.005         | 37.1353 | 56000 | 0.0240          | 0.9948   | 0.9974        | 0.9974           | 0.9981       | 0.9961        | 0.9975        | 0.9980         | 0.9965  | 0.9936   | 0.9951   | 0.9941    |
+| 0.0039        | 39.7878 | 60000 | 0.0244          | 0.9954   | 0.9977        | 0.9977           | 0.9967       | 0.9981        | 0.9980        | 0.9981         | 0.9953  | 0.9949   | 0.9951   | 0.9965    |
+| 0.0042        | 42.4403 | 64000 | 0.0203          | 0.9961   | 0.9980        | 0.9980           | 0.9982       | 0.9979        | 0.9982        | 0.9979         | 0.9972  | 0.9956   | 0.9954   | 0.9962    |
+| 0.0034        | 45.0928 | 68000 | 0.0165          | 0.9970   | 0.9985        | 0.9985           | 0.9984       | 0.9984        | 0.9984        | 0.9987         | 0.9976  | 0.9966   | 0.9962   | 0.9975    |
+| 0.0033        | 47.7454 | 72000 | 0.0105          | 0.9978   | 0.9989        | 0.9989           | 0.9991       | 0.9988        | 0.9988        | 0.9989         | 0.9983  | 0.9977   | 0.9978   | 0.9974    |
+
+
+### Framework versions
+
+- Transformers 4.48.3
+- Pytorch 2.1.0
+- Datasets 3.2.0
+- Tokenizers 0.21.0

config.json

@@ -0,0 +1,82 @@
+{
+  "_name_or_path": "nvidia/mit-b3",
+  "architectures": [
+    "SegformerForSemanticSegmentation"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "decoder_hidden_size": 768,
+  "depths": [
+    3,
+    4,
+    18,
+    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": "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"
+}

model.safetensors

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+size 188985928

training_args.bin

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