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README.md +93 -198
config.json +98 -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.
-- **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
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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. -->
-#### Preprocessing [optional]
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-#### Training Hyperparameters
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-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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-## Evaluation
-<!-- This section describes the evaluation protocols and provides the results. -->
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-#### Factors
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-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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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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-## Technical Specifications [optional]
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 ---
+license: other
+base_model: nvidia/mit-b3
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b2-seed63-apr-13-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-seed63-apr-13-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_401_6_lbls dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.7138
+- Mean Iou: 0.1266
+- Mean Accuracy: 0.2136
+- Overall Accuracy: 0.4273
+- Accuracy Unlabeled: nan
+- Accuracy Lv: 0.6939
+- Accuracy Rv: 0.0982
+- Accuracy Ra: 0.1706
+- Accuracy La: 0.5041
+- Accuracy Vs: 0.0
+- Accuracy As: 0.0
+- Accuracy Mk: 0.0
+- Accuracy Tk: nan
+- Accuracy Asd: 0.0557
+- Accuracy Vsd: 0.2283
+- Accuracy Ak: 0.3849
+- Iou Unlabeled: 0.0
+- Iou Lv: 0.4965
+- Iou Rv: 0.0899
+- Iou Ra: 0.1288
+- Iou La: 0.2845
+- Iou Vs: 0.0
+- Iou As: 0.0
+- Iou Mk: 0.0
+- Iou Tk: 0.0
+- Iou Asd: 0.0462
+- Iou Vsd: 0.1513
+- Iou Ak: 0.3225
+## 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-06
+- train_batch_size: 8
+- eval_batch_size: 8
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:------------:|:------------:|:-----------:|:-------------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:------:|:-------:|:-------:|:------:|
+| 2.5423        | 2.5   | 100  | 2.6367          | 0.0332   | 0.0976        | 0.0951           | nan                | 0.0612      | 0.0642      | 0.0301      | 0.1898      | 0.0         | 0.0         | 0.0086      | nan         | 0.0495       | 0.4697       | 0.1033      | 0.0           | 0.0573 | 0.0485 | 0.0262 | 0.1021 | 0.0    | 0.0    | 0.0019 | 0.0    | 0.0204  | 0.0612  | 0.0812 |
+| 2.3042        | 5.0   | 200  | 2.3925          | 0.0604   | 0.1412        | 0.1975           | nan                | 0.2435      | 0.0655      | 0.1292      | 0.2869      | 0.0         | 0.0         | 0.0046      | nan         | 0.0669       | 0.4894       | 0.1258      | 0.0           | 0.2144 | 0.0516 | 0.1074 | 0.1515 | 0.0    | 0.0    | 0.0017 | 0.0    | 0.0243  | 0.0670  | 0.1063 |
+| 2.0869        | 7.5   | 300  | 2.2183          | 0.0932   | 0.1839        | 0.3354           | nan                | 0.5208      | 0.0717      | 0.1836      | 0.4192      | 0.0         | 0.0         | 0.0006      | nan         | 0.0768       | 0.3608       | 0.2060      | 0.0           | 0.4077 | 0.0617 | 0.1436 | 0.2158 | 0.0    | 0.0    | 0.0003 | 0.0    | 0.0358  | 0.0787  | 0.1746 |
+| 2.0559        | 10.0  | 400  | 2.0298          | 0.1110   | 0.2055        | 0.3886           | nan                | 0.6144      | 0.1027      | 0.1815      | 0.4598      | 0.0         | 0.0         | 0.0005      | nan         | 0.0909       | 0.3011       | 0.3041      | 0.0           | 0.4559 | 0.0880 | 0.1400 | 0.2409 | 0.0    | 0.0    | 0.0003 | 0.0    | 0.0534  | 0.1001  | 0.2538 |
+| 1.9554        | 12.5  | 500  | 1.8871          | 0.1189   | 0.2111        | 0.4100           | nan                | 0.6561      | 0.1004      | 0.1647      | 0.4900      | 0.0         | 0.0         | 0.0009      | nan         | 0.0763       | 0.2611       | 0.3619      | 0.0           | 0.4739 | 0.0896 | 0.1263 | 0.2616 | 0.0    | 0.0    | 0.0007 | 0.0    | 0.0531  | 0.1207  | 0.3015 |
+| 2.0181        | 15.0  | 600  | 1.7720          | 0.1247   | 0.2139        | 0.4199           | nan                | 0.6735      | 0.1008      | 0.1723      | 0.4898      | 0.0         | 0.0         | 0.0         | nan         | 0.0706       | 0.2349       | 0.3972      | 0.0           | 0.4860 | 0.0912 | 0.1293 | 0.2720 | 0.0    | 0.0    | 0.0    | 0.0    | 0.0532  | 0.1386  | 0.3256 |
+| 1.6723        | 17.5  | 700  | 1.7386          | 0.1258   | 0.2129        | 0.4251           | nan                | 0.6860      | 0.1011      | 0.1724      | 0.5062      | 0.0         | 0.0         | 0.0         | nan         | 0.0615       | 0.2167       | 0.3848      | 0.0           | 0.4927 | 0.0917 | 0.1304 | 0.2814 | 0.0    | 0.0    | 0.0    | 0.0    | 0.0488  | 0.1426  | 0.3221 |
+| 1.5613        | 20.0  | 800  | 1.7751          | 0.1269   | 0.2151        | 0.4322           | nan                | 0.7050      | 0.1020      | 0.1730      | 0.5066      | 0.0         | 0.0         | 0.0         | nan         | 0.0570       | 0.2288       | 0.3788      | 0.0           | 0.4990 | 0.0927 | 0.1308 | 0.2841 | 0.0    | 0.0    | 0.0    | 0.0    | 0.0465  | 0.1502  | 0.3199 |
+| 1.5653        | 22.5  | 900  | 1.7222          | 0.1272   | 0.2142        | 0.4277           | nan                | 0.6924      | 0.1003      | 0.1794      | 0.5018      | 0.0         | 0.0         | 0.0         | nan         | 0.0568       | 0.2295       | 0.3814      | 0.0           | 0.4969 | 0.0914 | 0.1341 | 0.2837 | 0.0    | 0.0    | 0.0    | 0.0    | 0.0466  | 0.1523  | 0.3209 |
+| 1.5196        | 25.0  | 1000 | 1.7138          | 0.1266   | 0.2136        | 0.4273           | nan                | 0.6939      | 0.0982      | 0.1706      | 0.5041      | 0.0         | 0.0         | 0.0         | nan         | 0.0557       | 0.2283       | 0.3849      | 0.0           | 0.4965 | 0.0899 | 0.1288 | 0.2845 | 0.0    | 0.0    | 0.0    | 0.0    | 0.0462  | 0.1513  | 0.3225 |
+### 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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