NICOPOI-9
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segformer-b5-finetuned-ade20k-morphpadver1-hgo-coord_40epochs_distortion_ver2_global_norm

NICOPOI-9 commited on 9 days ago

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README.md +99 -199
config.json +82 -0
model.safetensors +3 -0
training_args.bin +3 -0

README.md CHANGED Viewed

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----
-library_name: transformers
-tags: []
----
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- 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
-Use the code below to get started with the model.
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-## Training Details
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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/segformer-b5-finetuned-ade-640-640
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b5-finetuned-ade20k-morphpadver1-hgo-coord_40epochs_distortion_ver2_global_norm
+  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-b5-finetuned-ade20k-morphpadver1-hgo-coord_40epochs_distortion_ver2_global_norm
+This model is a fine-tuned version of [nvidia/segformer-b5-finetuned-ade-640-640](https://huggingface.co/nvidia/segformer-b5-finetuned-ade-640-640) on the NICOPOI-9/Morphpad_HGO_1600_coord_global_norm dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1104
+- Mean Iou: 0.9755
+- Mean Accuracy: 0.9877
+- Overall Accuracy: 0.9875
+- Accuracy 0-0: 0.9892
+- Accuracy 0-90: 0.9855
+- Accuracy 90-0: 0.9863
+- Accuracy 90-90: 0.9897
+- Iou 0-0: 0.9778
+- Iou 0-90: 0.9741
+- Iou 90-0: 0.9734
+- Iou 90-90: 0.9766
+## 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: 40
+### 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 |
+|:-------------:|:-------:|:------:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:-------------:|:-------------:|:--------------:|:-------:|:--------:|:--------:|:---------:|
+| 1.3668        | 1.3680  | 4000   | 1.2660          | 0.2258   | 0.3802        | 0.3984           | 0.1901       | 0.4693        | 0.6808        | 0.1805         | 0.1537  | 0.2979   | 0.3155   | 0.1360    |
+| 0.8028        | 2.7360  | 8000   | 1.0729          | 0.3341   | 0.5062        | 0.5266           | 0.2943       | 0.7462        | 0.6891        | 0.2953         | 0.2476  | 0.4225   | 0.4118   | 0.2544    |
+| 0.9605        | 4.1040  | 12000  | 0.7966          | 0.5070   | 0.6678        | 0.6795           | 0.5623       | 0.7823        | 0.8018        | 0.5249         | 0.4831  | 0.5564   | 0.5338   | 0.4548    |
+| 0.59          | 5.4720  | 16000  | 0.5049          | 0.6944   | 0.8173        | 0.8197           | 0.7840       | 0.8640        | 0.8169        | 0.8043         | 0.6977  | 0.6983   | 0.6912   | 0.6906    |
+| 0.4359        | 6.8399  | 20000  | 0.3698          | 0.7779   | 0.8755        | 0.8748           | 0.8698       | 0.8828        | 0.8515        | 0.8977         | 0.7808  | 0.7776   | 0.7678   | 0.7855    |
+| 0.3519        | 8.2079  | 24000  | 0.3545          | 0.7831   | 0.8734        | 0.8785           | 0.8256       | 0.9371        | 0.9178        | 0.8129         | 0.7893  | 0.7908   | 0.7801   | 0.7721    |
+| 0.2117        | 9.5759  | 28000  | 0.2449          | 0.8532   | 0.9180        | 0.9205           | 0.8938       | 0.9490        | 0.9396        | 0.8894         | 0.8625  | 0.8530   | 0.8454   | 0.8520    |
+| 0.4507        | 10.9439 | 32000  | 0.2180          | 0.8723   | 0.9293        | 0.9315           | 0.9214       | 0.9632        | 0.9430        | 0.8894         | 0.8865  | 0.8644   | 0.8736   | 0.8645    |
+| 0.1921        | 12.3119 | 36000  | 0.1766          | 0.9018   | 0.9475        | 0.9480           | 0.9375       | 0.9644        | 0.9383        | 0.9499         | 0.9086  | 0.8969   | 0.8936   | 0.9081    |
+| 0.6741        | 13.6799 | 40000  | 0.1713          | 0.9009   | 0.9467        | 0.9478           | 0.9612       | 0.9654        | 0.9563        | 0.9037         | 0.9183  | 0.8975   | 0.9027   | 0.8852    |
+| 0.0979        | 15.0479 | 44000  | 0.1528          | 0.9257   | 0.9610        | 0.9612           | 0.9614       | 0.9568        | 0.9697        | 0.9560         | 0.9335  | 0.9255   | 0.9165   | 0.9273    |
+| 0.2138        | 16.4159 | 48000  | 0.1637          | 0.9177   | 0.9561        | 0.9568           | 0.9494       | 0.9608        | 0.9651        | 0.9492         | 0.9240  | 0.9101   | 0.9153   | 0.9214    |
+| 0.1426        | 17.7839 | 52000  | 0.1263          | 0.9454   | 0.9716        | 0.9718           | 0.9735       | 0.9734        | 0.9737        | 0.9659         | 0.9502  | 0.9438   | 0.9416   | 0.9460    |
+| 0.1079        | 19.1518 | 56000  | 0.1401          | 0.9299   | 0.9625        | 0.9635           | 0.9630       | 0.9705        | 0.9793        | 0.9370         | 0.9403  | 0.9339   | 0.9225   | 0.9227    |
+| 0.0968        | 20.5198 | 60000  | 0.1735          | 0.9231   | 0.9592        | 0.9600           | 0.9447       | 0.9648        | 0.9674        | 0.9600         | 0.9202  | 0.9239   | 0.9185   | 0.9300    |
+| 0.1719        | 21.8878 | 64000  | 0.1326          | 0.9459   | 0.9718        | 0.9720           | 0.9579       | 0.9696        | 0.9751        | 0.9848         | 0.9464  | 0.9406   | 0.9434   | 0.9530    |
+| 0.0587        | 23.2558 | 68000  | 0.1135          | 0.9585   | 0.9791        | 0.9786           | 0.9850       | 0.9710        | 0.9773        | 0.9831         | 0.9635  | 0.9542   | 0.9558   | 0.9603    |
+| 0.2671        | 24.6238 | 72000  | 0.1184          | 0.9548   | 0.9761        | 0.9768           | 0.9655       | 0.9823        | 0.9827        | 0.9742         | 0.9544  | 0.9576   | 0.9485   | 0.9587    |
+| 0.0418        | 25.9918 | 76000  | 0.1169          | 0.9605   | 0.9797        | 0.9797           | 0.9818       | 0.9765        | 0.9836        | 0.9768         | 0.9668  | 0.9574   | 0.9570   | 0.9608    |
+| 0.0587        | 27.3598 | 80000  | 0.1084          | 0.9590   | 0.9786        | 0.9790           | 0.9714       | 0.9810        | 0.9843        | 0.9776         | 0.9600  | 0.9586   | 0.9553   | 0.9623    |
+| 0.0067        | 28.7278 | 84000  | 0.1190          | 0.9641   | 0.9816        | 0.9815           | 0.9826       | 0.9775        | 0.9848        | 0.9815         | 0.9703  | 0.9629   | 0.9590   | 0.9641    |
+| 0.0369        | 30.0958 | 88000  | 0.1230          | 0.9644   | 0.9818        | 0.9818           | 0.9804       | 0.9822        | 0.9811        | 0.9834         | 0.9667  | 0.9613   | 0.9627   | 0.9670    |
+| 0.0814        | 31.4637 | 92000  | 0.1184          | 0.9664   | 0.9828        | 0.9828           | 0.9838       | 0.9827        | 0.9853        | 0.9792         | 0.9688  | 0.9674   | 0.9633   | 0.9661    |
+| 0.1671        | 32.8317 | 96000  | 0.1193          | 0.9676   | 0.9835        | 0.9834           | 0.9839       | 0.9820        | 0.9837        | 0.9845         | 0.9718  | 0.9652   | 0.9661   | 0.9674    |
+| 0.1289        | 34.1997 | 100000 | 0.1201          | 0.9620   | 0.9801        | 0.9806           | 0.9705       | 0.9845        | 0.9842        | 0.9811         | 0.9609  | 0.9588   | 0.9624   | 0.9657    |
+| 0.0551        | 35.5677 | 104000 | 0.1159          | 0.9707   | 0.9851        | 0.9850           | 0.9863       | 0.9831        | 0.9854        | 0.9856         | 0.9741  | 0.9680   | 0.9689   | 0.9717    |
+| 0.0217        | 36.9357 | 108000 | 0.1141          | 0.9732   | 0.9865        | 0.9863           | 0.9886       | 0.9826        | 0.9868        | 0.9879         | 0.9767  | 0.9705   | 0.9722   | 0.9733    |
+| 0.0031        | 38.3037 | 112000 | 0.1177          | 0.9735   | 0.9866        | 0.9865           | 0.9891       | 0.9843        | 0.9879        | 0.9849         | 0.9770  | 0.9724   | 0.9714   | 0.9733    |
+| 0.0435        | 39.6717 | 116000 | 0.1104          | 0.9755   | 0.9877        | 0.9875           | 0.9892       | 0.9855        | 0.9863        | 0.9897         | 0.9778  | 0.9741   | 0.9734   | 0.9766    |
+### 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/segformer-b5-finetuned-ade-640-640",
+  "architectures": [
+    "SegformerForSemanticSegmentation"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "decoder_hidden_size": 768,
+  "depths": [
+    3,
+    6,
+    40,
+    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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