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training_args.bin +3 -0

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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 Sources [optional]
-<!-- Provide the basic links for the model. -->
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-## Uses
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-### Direct Use
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-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
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-<!-- 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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-### Results
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-#### Summary
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-<!-- 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-b5
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer_Clean_Set1_95images_mit-b5
+  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_Clean_Set1_95images_mit-b5
+This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the Hasano20/Clean_Set1_95images dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0169
+- Mean Iou: 0.6481
+- Mean Accuracy: 0.9819
+- Overall Accuracy: 0.9935
+- Accuracy Background: nan
+- Accuracy Melt: 0.9668
+- Accuracy Substrate: 0.9970
+- Iou Background: 0.0
+- Iou Melt: 0.9507
+- Iou Substrate: 0.9937
+## 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: 0.0001
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 50
+### Training results
+| Training Loss | Epoch   | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Melt | Accuracy Substrate | Iou Background | Iou Melt | Iou Substrate |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:------------------:|:--------------:|:--------:|:-------------:|
+| 0.2276        | 1.1765  | 20   | 0.2657          | 0.3456   | 0.5675        | 0.8925           | nan                 | 0.1416        | 0.9935             | 0.0            | 0.1374   | 0.8994        |
+| 0.3964        | 2.3529  | 40   | 0.1808          | 0.3540   | 0.5688        | 0.8852           | nan                 | 0.1542        | 0.9835             | 0.0            | 0.1476   | 0.9145        |
+| 0.2669        | 3.5294  | 60   | 0.1312          | 0.3929   | 0.6246        | 0.9080           | nan                 | 0.2530        | 0.9961             | 0.0            | 0.2488   | 0.9298        |
+| 0.0785        | 4.7059  | 80   | 0.1141          | 0.4822   | 0.7742        | 0.9255           | nan                 | 0.5758        | 0.9725             | 0.0            | 0.4933   | 0.9533        |
+| 0.1552        | 5.8824  | 100  | 0.0904          | 0.5549   | 0.9259        | 0.9567           | nan                 | 0.8857        | 0.9662             | 0.0            | 0.7116   | 0.9532        |
+| 0.1163        | 7.0588  | 120  | 0.0988          | 0.5169   | 0.8101        | 0.9463           | nan                 | 0.6316        | 0.9886             | 0.0            | 0.6060   | 0.9446        |
+| 0.0738        | 8.2353  | 140  | 0.2555          | 0.3735   | 0.6075        | 0.9064           | nan                 | 0.2156        | 0.9993             | 0.0            | 0.2152   | 0.9053        |
+| 0.07          | 9.4118  | 160  | 0.0706          | 0.5411   | 0.8335        | 0.9589           | nan                 | 0.6691        | 0.9979             | 0.0            | 0.6629   | 0.9605        |
+| 0.0432        | 10.5882 | 180  | 0.0542          | 0.5821   | 0.8942        | 0.9708           | nan                 | 0.7937        | 0.9946             | 0.0            | 0.7743   | 0.9720        |
+| 0.0833        | 11.7647 | 200  | 0.0554          | 0.5863   | 0.8937        | 0.9736           | nan                 | 0.7890        | 0.9984             | 0.0            | 0.7823   | 0.9765        |
+| 0.0488        | 12.9412 | 220  | 0.0325          | 0.6218   | 0.9654        | 0.9824           | nan                 | 0.9431        | 0.9877             | 0.0            | 0.8817   | 0.9836        |
+| 0.0401        | 14.1176 | 240  | 0.0409          | 0.6276   | 0.9531        | 0.9874           | nan                 | 0.9081        | 0.9981             | 0.0            | 0.8966   | 0.9863        |
+| 0.0192        | 15.2941 | 260  | 0.0219          | 0.6383   | 0.9686        | 0.9902           | nan                 | 0.9402        | 0.9969             | 0.0            | 0.9242   | 0.9908        |
+| 0.0639        | 16.4706 | 280  | 0.0500          | 0.5965   | 0.9125        | 0.9749           | nan                 | 0.8306        | 0.9943             | 0.0            | 0.8014   | 0.9882        |
+| 0.0237        | 17.6471 | 300  | 0.0246          | 0.6300   | 0.9558        | 0.9864           | nan                 | 0.9156        | 0.9959             | 0.0            | 0.9005   | 0.9894        |
+| 0.014         | 18.8235 | 320  | 0.0207          | 0.6441   | 0.9757        | 0.9921           | nan                 | 0.9543        | 0.9971             | 0.0            | 0.9404   | 0.9920        |
+| 0.0362        | 20.0    | 340  | 0.0226          | 0.6348   | 0.9639        | 0.9888           | nan                 | 0.9312        | 0.9966             | 0.0            | 0.9157   | 0.9889        |
+| 0.0195        | 21.1765 | 360  | 0.0203          | 0.6437   | 0.9754        | 0.9923           | nan                 | 0.9532        | 0.9976             | 0.0            | 0.9392   | 0.9919        |
+| 0.0123        | 22.3529 | 380  | 0.0176          | 0.6415   | 0.9745        | 0.9910           | nan                 | 0.9529        | 0.9962             | 0.0            | 0.9317   | 0.9929        |
+| 0.0103        | 23.5294 | 400  | 0.0212          | 0.6427   | 0.9781        | 0.9918           | nan                 | 0.9600        | 0.9961             | 0.0            | 0.9364   | 0.9916        |
+| 0.0098        | 24.7059 | 420  | 0.0157          | 0.6467   | 0.9831        | 0.9929           | nan                 | 0.9702        | 0.9960             | 0.0            | 0.9465   | 0.9935        |
+| 0.0074        | 25.8824 | 440  | 0.0168          | 0.6438   | 0.9730        | 0.9920           | nan                 | 0.9482        | 0.9979             | 0.0            | 0.9384   | 0.9930        |
+| 0.0078        | 27.0588 | 460  | 0.0179          | 0.6441   | 0.9752        | 0.9922           | nan                 | 0.9530        | 0.9974             | 0.0            | 0.9396   | 0.9926        |
+| 0.0084        | 28.2353 | 480  | 0.0188          | 0.6416   | 0.9808        | 0.9909           | nan                 | 0.9675        | 0.9941             | 0.0            | 0.9333   | 0.9916        |
+| 0.0096        | 29.4118 | 500  | 0.0187          | 0.6449   | 0.9866        | 0.9924           | nan                 | 0.9790        | 0.9942             | 0.0            | 0.9422   | 0.9923        |
+| 0.0059        | 30.5882 | 520  | 0.0209          | 0.6415   | 0.9718        | 0.9914           | nan                 | 0.9460        | 0.9975             | 0.0            | 0.9331   | 0.9915        |
+| 0.0092        | 31.7647 | 540  | 0.0227          | 0.6383   | 0.9652        | 0.9903           | nan                 | 0.9323        | 0.9981             | 0.0            | 0.9239   | 0.9910        |
+| 0.0107        | 32.9412 | 560  | 0.0177          | 0.6438   | 0.9747        | 0.9920           | nan                 | 0.9521        | 0.9973             | 0.0            | 0.9382   | 0.9931        |
+| 0.0092        | 34.1176 | 580  | 0.0167          | 0.6463   | 0.9771        | 0.9929           | nan                 | 0.9563        | 0.9979             | 0.0            | 0.9455   | 0.9934        |
+| 0.0076        | 35.2941 | 600  | 0.0160          | 0.6472   | 0.9791        | 0.9931           | nan                 | 0.9609        | 0.9974             | 0.0            | 0.9479   | 0.9937        |
+| 0.0062        | 36.4706 | 620  | 0.0193          | 0.6423   | 0.9715        | 0.9917           | nan                 | 0.9450        | 0.9979             | 0.0            | 0.9350   | 0.9919        |
+| 0.0063        | 37.6471 | 640  | 0.0160          | 0.6481   | 0.9824        | 0.9933           | nan                 | 0.9680        | 0.9967             | 0.0            | 0.9503   | 0.9939        |
+| 0.0064        | 38.8235 | 660  | 0.0164          | 0.6489   | 0.9846        | 0.9935           | nan                 | 0.9730        | 0.9963             | 0.0            | 0.9530   | 0.9936        |
+| 0.009         | 40.0    | 680  | 0.0167          | 0.6487   | 0.9829        | 0.9937           | nan                 | 0.9687        | 0.9971             | 0.0            | 0.9521   | 0.9938        |
+| 0.0062        | 41.1765 | 700  | 0.0169          | 0.6478   | 0.9801        | 0.9934           | nan                 | 0.9626        | 0.9975             | 0.0            | 0.9497   | 0.9936        |
+| 0.0047        | 42.3529 | 720  | 0.0170          | 0.6481   | 0.9814        | 0.9934           | nan                 | 0.9657        | 0.9972             | 0.0            | 0.9507   | 0.9935        |
+| 0.0053        | 43.5294 | 740  | 0.0166          | 0.6490   | 0.9832        | 0.9939           | nan                 | 0.9693        | 0.9972             | 0.0            | 0.9529   | 0.9941        |
+| 0.0076        | 44.7059 | 760  | 0.0165          | 0.6484   | 0.9828        | 0.9934           | nan                 | 0.9688        | 0.9968             | 0.0            | 0.9513   | 0.9938        |
+| 0.0066        | 45.8824 | 780  | 0.0166          | 0.6488   | 0.9835        | 0.9937           | nan                 | 0.9702        | 0.9969             | 0.0            | 0.9523   | 0.9940        |
+| 0.0048        | 47.0588 | 800  | 0.0169          | 0.6482   | 0.9824        | 0.9935           | nan                 | 0.9678        | 0.9969             | 0.0            | 0.9508   | 0.9937        |
+| 0.0061        | 48.2353 | 820  | 0.0170          | 0.6481   | 0.9821        | 0.9934           | nan                 | 0.9674        | 0.9969             | 0.0            | 0.9506   | 0.9937        |
+| 0.0087        | 49.4118 | 840  | 0.0169          | 0.6481   | 0.9819        | 0.9935           | nan                 | 0.9668        | 0.9970             | 0.0            | 0.9507   | 0.9937        |
+### Framework versions
+- Transformers 4.41.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.19.2
+- Tokenizers 0.19.1

config.json ADDED Viewed

	@@ -0,0 +1,80 @@

+{
+  "_name_or_path": "nvidia/mit-b5",
+  "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": "background",
+    "1": "melt",
+    "2": "substrate"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "background": 0,
+    "melt": 1,
+    "substrate": 2
+  },
+  "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": "4.41.2"
+}

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