NICOPOI-9
/

segformer-b0-finetuned-morphpadver1-hgo-30-coord-v3_120epochs

@@ -1,199 +1,98 @@
----
-library_name: transformers
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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-b0-finetuned-morphpadver1-hgo-30-coord-v3_120epochs
+  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-30-coord-v3_120epochs
+This model is a fine-tuned version of [nvidia/mit-b3](https://huggingface.co/nvidia/mit-b3) on the NICOPOI-9/morphpad_coord_hgo_30_30_512_4class dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3128
+- Mean Iou: 0.7857
+- Mean Accuracy: 0.8800
+- Overall Accuracy: 0.8799
+- Accuracy 0-0: 0.8782
+- Accuracy 0-90: 0.8842
+- Accuracy 90-0: 0.8809
+- Accuracy 90-90: 0.8765
+- Iou 0-0: 0.7869
+- Iou 0-90: 0.7762
+- Iou 90-0: 0.7880
+- Iou 90-90: 0.7916
+## 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: 120
+### 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 |
+|:-------------:|:--------:|:------:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:-------------:|:-------------:|:--------------:|:-------:|:--------:|:--------:|:---------:|
+| 1.188         | 4.2105   | 4000   | 1.2023          | 0.2499   | 0.3996        | 0.3995           | 0.3256       | 0.4999        | 0.4603        | 0.3124         | 0.2510  | 0.2542   | 0.2429   | 0.2514    |
+| 0.9829        | 8.4211   | 8000   | 0.9446          | 0.3676   | 0.5326        | 0.5326           | 0.4568       | 0.5068        | 0.7157        | 0.4508         | 0.3872  | 0.3492   | 0.3434   | 0.3907    |
+| 0.7539        | 12.6316  | 12000  | 0.7804          | 0.4475   | 0.6163        | 0.6168           | 0.5690       | 0.6618        | 0.5314        | 0.7030         | 0.4806  | 0.4244   | 0.4335   | 0.4513    |
+| 0.969         | 16.8421  | 16000  | 0.6554          | 0.5152   | 0.6775        | 0.6780           | 0.6172       | 0.7013        | 0.6543        | 0.7372         | 0.5533  | 0.4849   | 0.5090   | 0.5136    |
+| 0.5649        | 21.0526  | 20000  | 0.5879          | 0.5597   | 0.7156        | 0.7157           | 0.6964       | 0.7740        | 0.6842        | 0.7078         | 0.5869  | 0.5181   | 0.5555   | 0.5782    |
+| 0.5983        | 25.2632  | 24000  | 0.5229          | 0.5963   | 0.7464        | 0.7460           | 0.8236       | 0.7139        | 0.7132        | 0.7348         | 0.5647  | 0.6058   | 0.6038   | 0.6110    |
+| 0.5077        | 29.4737  | 28000  | 0.4971          | 0.6133   | 0.7587        | 0.7585           | 0.7767       | 0.7577        | 0.7964        | 0.7042         | 0.6236  | 0.6053   | 0.5724   | 0.6519    |
+| 0.456         | 33.6842  | 32000  | 0.4880          | 0.6346   | 0.7763        | 0.7764           | 0.7792       | 0.7575        | 0.7675        | 0.8011         | 0.6434  | 0.6257   | 0.6376   | 0.6317    |
+| 0.4278        | 37.8947  | 36000  | 0.4139          | 0.6688   | 0.8015        | 0.8014           | 0.8149       | 0.7962        | 0.8101        | 0.7849         | 0.6663  | 0.6599   | 0.6611   | 0.6880    |
+| 0.4974        | 42.1053  | 40000  | 0.3921          | 0.6863   | 0.8132        | 0.8132           | 0.7997       | 0.8370        | 0.8165        | 0.7996         | 0.7065  | 0.6548   | 0.6794   | 0.7046    |
+| 0.4364        | 46.3158  | 44000  | 0.3697          | 0.7023   | 0.8244        | 0.8247           | 0.7941       | 0.8293        | 0.8225        | 0.8520         | 0.7248  | 0.6884   | 0.6982   | 0.6978    |
+| 0.3254        | 50.5263  | 48000  | 0.3521          | 0.7152   | 0.8340        | 0.8338           | 0.8529       | 0.8268        | 0.8315        | 0.8247         | 0.7016  | 0.7133   | 0.7162   | 0.7295    |
+| 0.3139        | 54.7368  | 52000  | 0.3471          | 0.7224   | 0.8386        | 0.8386           | 0.8343       | 0.8526        | 0.8305        | 0.8371         | 0.7209  | 0.7032   | 0.7306   | 0.7347    |
+| 0.3209        | 58.9474  | 56000  | 0.3253          | 0.7359   | 0.8479        | 0.8479           | 0.8565       | 0.8363        | 0.8525        | 0.8463         | 0.7340  | 0.7348   | 0.7294   | 0.7455    |
+| 0.2815        | 63.1579  | 60000  | 0.3234          | 0.7421   | 0.8516        | 0.8516           | 0.8468       | 0.8707        | 0.8431        | 0.8459         | 0.7466  | 0.7148   | 0.7463   | 0.7608    |
+| 0.3002        | 67.3684  | 64000  | 0.3132          | 0.7520   | 0.8584        | 0.8584           | 0.8545       | 0.8623        | 0.8503        | 0.8663         | 0.7544  | 0.7411   | 0.7560   | 0.7566    |
+| 0.2874        | 71.5789  | 68000  | 0.3068          | 0.7571   | 0.8615        | 0.8615           | 0.8582       | 0.8814        | 0.8540        | 0.8524         | 0.7628  | 0.7325   | 0.7639   | 0.7693    |
+| 1.0781        | 75.7895  | 72000  | 0.3185          | 0.7524   | 0.8588        | 0.8586           | 0.8755       | 0.8528        | 0.8649        | 0.8419         | 0.7446  | 0.7461   | 0.7503   | 0.7686    |
+| 0.2688        | 80.0     | 76000  | 0.2993          | 0.7663   | 0.8676        | 0.8676           | 0.8688       | 0.8677        | 0.8639        | 0.8702         | 0.7693  | 0.7553   | 0.7674   | 0.7730    |
+| 0.2566        | 84.2105  | 80000  | 0.2962          | 0.7696   | 0.8698        | 0.8698           | 0.8669       | 0.8687        | 0.8673        | 0.8761         | 0.7729  | 0.7574   | 0.7739   | 0.7744    |
+| 0.2556        | 88.4211  | 84000  | 0.2985          | 0.7754   | 0.8735        | 0.8735           | 0.8735       | 0.8679        | 0.8799        | 0.8726         | 0.7767  | 0.7676   | 0.7734   | 0.7839    |
+| 0.2402        | 92.6316  | 88000  | 0.2976          | 0.7786   | 0.8755        | 0.8755           | 0.8786       | 0.8751        | 0.8694        | 0.8790         | 0.7766  | 0.7711   | 0.7810   | 0.7858    |
+| 0.286         | 96.8421  | 92000  | 0.2998          | 0.7803   | 0.8766        | 0.8766           | 0.8733       | 0.8750        | 0.8828        | 0.8752         | 0.7833  | 0.7733   | 0.7770   | 0.7876    |
+| 0.1853        | 101.0526 | 96000  | 0.2987          | 0.7843   | 0.8791        | 0.8791           | 0.8810       | 0.8816        | 0.8813        | 0.8726         | 0.7811  | 0.7754   | 0.7870   | 0.7935    |
+| 0.2401        | 105.2632 | 100000 | 0.3093          | 0.7819   | 0.8776        | 0.8776           | 0.8761       | 0.8820        | 0.8791        | 0.8732         | 0.7818  | 0.7701   | 0.7864   | 0.7893    |
+| 0.2546        | 109.4737 | 104000 | 0.3095          | 0.7846   | 0.8793        | 0.8793           | 0.8819       | 0.8829        | 0.8756        | 0.8766         | 0.7850  | 0.7731   | 0.7891   | 0.7912    |
+| 0.3595        | 113.6842 | 108000 | 0.3096          | 0.7857   | 0.8800        | 0.8800           | 0.8777       | 0.8820        | 0.8795        | 0.8806         | 0.7858  | 0.7766   | 0.7892   | 0.7912    |
+| 0.2484        | 117.8947 | 112000 | 0.3128          | 0.7857   | 0.8800        | 0.8799           | 0.8782       | 0.8842        | 0.8809        | 0.8765         | 0.7869  | 0.7762   | 0.7880   | 0.7916    |
+### 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-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"
+}

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