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README.md +93 -198
config.json +98 -0
model.safetensors +3 -0
training_args.bin +3 -0

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@@ -1,201 +1,96 @@
 ---
-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.
-- **Developed by:** [More Information Needed]
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-- **Model type:** [More Information Needed]
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-### Model Sources [optional]
-<!-- Provide the basic links for the model. -->
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-## Uses
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-### Direct Use
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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-### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-## How to Get Started with the Model
-Use the code below to get started with the model.
-[More Information Needed]
-## Training Details
-### Training Data
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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-### Training Procedure
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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-#### Training Hyperparameters
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-#### Factors
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-### Results
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-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
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-## Environmental Impact
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-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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 ---
+license: other
+base_model: nvidia/mit-b3
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b2-seed-67-v1
+  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-b2-seed-67-v1
+This model is a fine-tuned version of [nvidia/mit-b3](https://huggingface.co/nvidia/mit-b3) on the unreal-hug/REAL_DATASET_SEG_331 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4746
+- Mean Iou: 0.2841
+- Mean Accuracy: 0.3507
+- Overall Accuracy: 0.6084
+- Accuracy Unlabeled: nan
+- Accuracy Lv: 0.7915
+- Accuracy Rv: 0.4646
+- Accuracy Ra: 0.4834
+- Accuracy La: 0.6858
+- Accuracy Vs: 0.0
+- Accuracy As: 0.0
+- Accuracy Mk: 0.0
+- Accuracy Tk: nan
+- Accuracy Asd: 0.3160
+- Accuracy Vsd: 0.2747
+- Accuracy Ak: 0.4910
+- Iou Unlabeled: 0.0
+- Iou Lv: 0.7252
+- Iou Rv: 0.4232
+- Iou Ra: 0.4411
+- Iou La: 0.5427
+- Iou Vs: 0.0
+- Iou As: 0.0
+- Iou Mk: 0.0
+- Iou Tk: nan
+- Iou Asd: 0.2832
+- Iou Vsd: 0.2342
+- Iou Ak: 0.4759
+## 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: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.05
+- training_steps: 1000
+### Training results
+| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Lv | Accuracy Rv | Accuracy Ra | Accuracy La | Accuracy Vs | Accuracy As | Accuracy Mk | Accuracy Tk | Accuracy Asd | Accuracy Vsd | Accuracy Ak | Iou Unlabeled | Iou Lv | Iou Rv | Iou Ra | Iou La | Iou Vs | Iou As | Iou Mk | Iou Tk | Iou Asd | Iou Vsd | Iou Ak |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:------------:|:------------:|:-----------:|:-------------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:-------:|:-------:|:------:|
+| 1.2449        | 5.88  | 100  | 1.1508          | 0.1187   | 0.1954        | 0.4575           | nan                | 0.8193      | 0.0533      | 0.1371      | 0.5424      | 0.0         | 0.0         | 0.0         | nan         | 0.0171       | 0.0155       | 0.3697      | 0.0           | 0.5501 | 0.0518 | 0.1253 | 0.3509 | 0.0    | 0.0    | 0.0    | 0.0    | 0.0170  | 0.0148  | 0.3145 |
+| 0.7118        | 11.76 | 200  | 0.7012          | 0.1534   | 0.2007        | 0.4466           | nan                | 0.7352      | 0.1138      | 0.2300      | 0.5548      | 0.0         | 0.0         | 0.0         | nan         | 0.0168       | 0.0284       | 0.3280      | 0.0           | 0.6079 | 0.1081 | 0.2084 | 0.4120 | 0.0    | 0.0    | 0.0    | nan    | 0.0167  | 0.0276  | 0.3064 |
+| 0.5567        | 17.65 | 300  | 0.5686          | 0.1896   | 0.2372        | 0.4810           | nan                | 0.6994      | 0.2332      | 0.3522      | 0.5913      | 0.0         | 0.0         | 0.0         | nan         | 0.0389       | 0.0765       | 0.3806      | 0.0           | 0.6382 | 0.2142 | 0.3023 | 0.4563 | 0.0    | 0.0    | 0.0    | nan    | 0.0386  | 0.0714  | 0.3649 |
+| 0.5054        | 23.53 | 400  | 0.5441          | 0.2473   | 0.3075        | 0.5803           | nan                | 0.7991      | 0.4241      | 0.4885      | 0.5970      | 0.0         | 0.0         | 0.0         | nan         | 0.1535       | 0.1388       | 0.4745      | 0.0           | 0.7215 | 0.3725 | 0.4107 | 0.4908 | 0.0    | 0.0    | 0.0    | nan    | 0.1486  | 0.1228  | 0.4537 |
+| 0.4344        | 29.41 | 500  | 0.5188          | 0.2706   | 0.3382        | 0.5967           | nan                | 0.7810      | 0.4337      | 0.4668      | 0.7031      | 0.0         | 0.0         | 0.0         | nan         | 0.2612       | 0.2644       | 0.4721      | 0.0           | 0.7121 | 0.3916 | 0.4164 | 0.5372 | 0.0    | 0.0    | 0.0    | nan    | 0.2398  | 0.2236  | 0.4558 |
+| 0.3796        | 35.29 | 600  | 0.5032          | 0.2669   | 0.3315        | 0.5911           | nan                | 0.7953      | 0.4343      | 0.4050      | 0.6920      | 0.0         | 0.0         | 0.0         | nan         | 0.2841       | 0.2321       | 0.4717      | 0.0           | 0.7196 | 0.3965 | 0.3778 | 0.5273 | 0.0    | 0.0    | 0.0    | nan    | 0.2589  | 0.1996  | 0.4568 |
+| 0.3888        | 41.18 | 700  | 0.4801          | 0.2798   | 0.3461        | 0.6037           | nan                | 0.7862      | 0.4532      | 0.4667      | 0.6983      | 0.0         | 0.0         | 0.0         | nan         | 0.3065       | 0.2590       | 0.4908      | 0.0           | 0.7192 | 0.4127 | 0.4292 | 0.5444 | 0.0    | 0.0    | 0.0    | nan    | 0.2756  | 0.2216  | 0.4746 |
+| 0.3467        | 47.06 | 800  | 0.4753          | 0.2822   | 0.3478        | 0.6061           | nan                | 0.7919      | 0.4585      | 0.4857      | 0.6814      | 0.0         | 0.0         | 0.0         | nan         | 0.3131       | 0.2640       | 0.4831      | 0.0           | 0.7259 | 0.4196 | 0.4424 | 0.5402 | 0.0    | 0.0    | 0.0    | nan    | 0.2813  | 0.2262  | 0.4685 |
+| 0.3757        | 52.94 | 900  | 0.4746          | 0.2841   | 0.3507        | 0.6084           | nan                | 0.7915      | 0.4646      | 0.4834      | 0.6858      | 0.0         | 0.0         | 0.0         | nan         | 0.3160       | 0.2747       | 0.4910      | 0.0           | 0.7252 | 0.4232 | 0.4411 | 0.5427 | 0.0    | 0.0    | 0.0    | nan    | 0.2832  | 0.2342  | 0.4759 |
+| 0.3616        | 58.82 | 1000 | 0.4788          | 0.2860   | 0.3537        | 0.6116           | nan                | 0.7931      | 0.4687      | 0.4837      | 0.6922      | 0.0         | 0.0         | 0.0         | nan         | 0.3193       | 0.2830       | 0.4970      | 0.0           | 0.7262 | 0.4259 | 0.4411 | 0.5449 | 0.0    | 0.0    | 0.0    | nan    | 0.2856  | 0.2407  | 0.4817 |
+### Framework versions
+- Transformers 4.37.2
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

config.json ADDED Viewed

	@@ -0,0 +1,98 @@

+{
+  "_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": "unlabeled",
+    "1": "LV",
+    "2": "RV",
+    "3": "RA",
+    "4": "LA",
+    "5": "VS",
+    "6": "AS",
+    "7": "MK",
+    "8": "TK",
+    "9": "ASD",
+    "10": "VSD",
+    "11": "AK"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "AK": 11,
+    "AS": 6,
+    "ASD": 9,
+    "LA": 4,
+    "LV": 1,
+    "MK": 7,
+    "RA": 3,
+    "RV": 2,
+    "TK": 8,
+    "VS": 5,
+    "VSD": 10,
+    "unlabeled": 0
+  },
+  "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": "4.37.2"
+}

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