End of training

README.md

@@ -1,199 +1,93 @@
----
-library_name: transformers
-tags: []
----
-
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
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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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+---
+library_name: transformers
+license: other
+base_model: nvidia/mit-b2
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b0-finetuned-morphpadver1-hgo-coord-v2
+  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-hgo-coord-v2
+
+This model is a fine-tuned version of [nvidia/mit-b2](https://huggingface.co/nvidia/mit-b2) on the NICOPOI-9/morphpad_coord_hgo_512_4class dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2286
+- Mean Iou: 0.8128
+- Mean Accuracy: 0.8969
+- Overall Accuracy: 0.8968
+- Accuracy 0-0: 0.9119
+- Accuracy 0-90: 0.8833
+- Accuracy 90-0: 0.8951
+- Accuracy 90-90: 0.8974
+- Iou 0-0: 0.8200
+- Iou 0-90: 0.8185
+- Iou 90-0: 0.8144
+- Iou 90-90: 0.7983
+
+## 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: 60
+
+### 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 |
+|:-------------:|:-------:|:-----:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:-------------:|:-------------:|:--------------:|:-------:|:--------:|:--------:|:---------:|
+| 1.1507        | 2.5445  | 4000  | 1.1730          | 0.2502   | 0.4074        | 0.4084           | 0.4143       | 0.2410        | 0.6535        | 0.3208         | 0.2753  | 0.2079   | 0.2790   | 0.2385    |
+| 1.0135        | 5.0891  | 8000  | 0.9857          | 0.3270   | 0.4992        | 0.4961           | 0.6108       | 0.4085        | 0.3399        | 0.6378         | 0.3508  | 0.3116   | 0.3093   | 0.3363    |
+| 0.8651        | 7.6336  | 12000 | 0.8655          | 0.3997   | 0.5634        | 0.5652           | 0.4675       | 0.8101        | 0.4588        | 0.5172         | 0.4234  | 0.3705   | 0.3925   | 0.4123    |
+| 0.7904        | 10.1781 | 16000 | 0.7801          | 0.4485   | 0.6141        | 0.6147           | 0.5644       | 0.4939        | 0.8116        | 0.5863         | 0.4541  | 0.4593   | 0.4161   | 0.4645    |
+| 0.9002        | 12.7226 | 20000 | 0.7177          | 0.4769   | 0.6460        | 0.6457           | 0.6775       | 0.6256        | 0.6334        | 0.6475         | 0.4691  | 0.4874   | 0.4857   | 0.4657    |
+| 0.6111        | 15.2672 | 24000 | 0.6339          | 0.5288   | 0.6790        | 0.6814           | 0.6149       | 0.9232        | 0.6051        | 0.5727         | 0.5528  | 0.4628   | 0.5587   | 0.5409    |
+| 0.5422        | 17.8117 | 28000 | 0.5576          | 0.5788   | 0.7312        | 0.7300           | 0.6673       | 0.7190        | 0.6918        | 0.8469         | 0.6206  | 0.5811   | 0.5793   | 0.5340    |
+| 0.5594        | 20.3562 | 32000 | 0.5073          | 0.6016   | 0.7470        | 0.7482           | 0.7632       | 0.7259        | 0.8431        | 0.6558         | 0.5749  | 0.6233   | 0.5720   | 0.6361    |
+| 0.6542        | 22.9008 | 36000 | 0.4921          | 0.6137   | 0.7580        | 0.7590           | 0.7073       | 0.8514        | 0.7415        | 0.7320         | 0.6381  | 0.5894   | 0.6460   | 0.5813    |
+| 0.4827        | 25.4453 | 40000 | 0.4701          | 0.6321   | 0.7736        | 0.7730           | 0.7499       | 0.7378        | 0.7800        | 0.8268         | 0.6531  | 0.6572   | 0.6355   | 0.5827    |
+| 0.3901        | 27.9898 | 44000 | 0.4068          | 0.6747   | 0.8050        | 0.8052           | 0.8030       | 0.7737        | 0.8480        | 0.7955         | 0.6972  | 0.6956   | 0.6582   | 0.6477    |
+| 0.4725        | 30.5344 | 48000 | 0.3738          | 0.6928   | 0.8180        | 0.8180           | 0.8152       | 0.7977        | 0.8433        | 0.8158         | 0.7242  | 0.7024   | 0.6954   | 0.6492    |
+| 0.3067        | 33.0789 | 52000 | 0.3493          | 0.7223   | 0.8367        | 0.8374           | 0.8139       | 0.8374        | 0.8924        | 0.8029         | 0.7510  | 0.7253   | 0.6839   | 0.7290    |
+| 0.4898        | 35.6234 | 56000 | 0.3349          | 0.7197   | 0.8369        | 0.8368           | 0.8726       | 0.8097        | 0.8431        | 0.8221         | 0.7006  | 0.7348   | 0.7254   | 0.7179    |
+| 0.2826        | 38.1679 | 60000 | 0.3021          | 0.7503   | 0.8563        | 0.8569           | 0.8839       | 0.8769        | 0.8603        | 0.8041         | 0.7457  | 0.7359   | 0.7530   | 0.7668    |
+| 0.3235        | 40.7125 | 64000 | 0.2863          | 0.7561   | 0.8612        | 0.8610           | 0.8758       | 0.8490        | 0.8598        | 0.8601         | 0.7478  | 0.7821   | 0.7630   | 0.7316    |
+| 0.3374        | 43.2570 | 68000 | 0.2927          | 0.7689   | 0.8668        | 0.8674           | 0.8621       | 0.8328        | 0.9457        | 0.8266         | 0.7827  | 0.8025   | 0.7194   | 0.7708    |
+| 0.2588        | 45.8015 | 72000 | 0.2737          | 0.7743   | 0.8716        | 0.8717           | 0.9129       | 0.8702        | 0.8653        | 0.8380         | 0.7254  | 0.7849   | 0.8016   | 0.7852    |
+| 0.5224        | 48.3461 | 76000 | 0.2579          | 0.7905   | 0.8819        | 0.8822           | 0.9212       | 0.8628        | 0.9067        | 0.8367         | 0.7605  | 0.8124   | 0.7815   | 0.8075    |
+| 0.2171        | 50.8906 | 80000 | 0.2373          | 0.7971   | 0.8867        | 0.8870           | 0.9187       | 0.8895        | 0.8875        | 0.8512         | 0.7941  | 0.7931   | 0.7986   | 0.8025    |
+| 0.2075        | 53.4351 | 84000 | 0.2374          | 0.8051   | 0.8912        | 0.8916           | 0.9032       | 0.9120        | 0.8891        | 0.8608         | 0.8289  | 0.7819   | 0.8033   | 0.8064    |
+| 0.3577        | 55.9796 | 88000 | 0.2390          | 0.8081   | 0.8931        | 0.8935           | 0.9098       | 0.9007        | 0.9072        | 0.8545         | 0.8076  | 0.7889   | 0.8134   | 0.8224    |
+| 0.2084        | 58.5242 | 92000 | 0.2286          | 0.8128   | 0.8969        | 0.8968           | 0.9119       | 0.8833        | 0.8951        | 0.8974         | 0.8200  | 0.8185   | 0.8144   | 0.7983    |
+
+
+### 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-b2",
+  "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": "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 109450168

training_args.bin

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