End of training

README.md

@@ -1,199 +1,87 @@
 ---
-library_name: transformers
-tags: []
+license: other
+base_model: nvidia/mit-b5
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: SegFormer_Mixed_Set2_Grayscale_mit-b5
+  results: []
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
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-
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-## Model Details
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-### Model Description
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-<!-- Provide a longer summary of what this model is. -->
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-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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+<!-- 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_Mixed_Set2_Grayscale_mit-b5
+
+This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the Hasano20/Mixed_Set2_Grayscale dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0178
+- Mean Iou: 0.9762
+- Mean Accuracy: 0.9867
+- Overall Accuracy: 0.9938
+- Accuracy Background: 0.9926
+- Accuracy Melt: 0.9695
+- Accuracy Substrate: 0.9981
+- Iou Background: 0.9905
+- Iou Melt: 0.9469
+- Iou Substrate: 0.9913
+
+## 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: 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_steps: 100
+- 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 |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:------------------:|:--------------:|:--------:|:-------------:|
+| 0.2842        | 0.7042  | 50   | 0.1653          | 0.7872   | 0.8326        | 0.9457           | 0.9693              | 0.5454        | 0.9831             | 0.9409         | 0.4996   | 0.9212        |
+| 0.0534        | 1.4085  | 100  | 0.0704          | 0.9016   | 0.9292        | 0.9751           | 0.9884              | 0.8114        | 0.9878             | 0.9688         | 0.7722   | 0.9639        |
+| 0.0309        | 2.1127  | 150  | 0.0424          | 0.9389   | 0.9618        | 0.9854           | 0.9948              | 0.9004        | 0.9901             | 0.9808         | 0.8551   | 0.9807        |
+| 0.0358        | 2.8169  | 200  | 0.0390          | 0.9443   | 0.9710        | 0.9858           | 0.9797              | 0.9360        | 0.9972             | 0.9778         | 0.8732   | 0.9820        |
+| 0.031         | 3.5211  | 250  | 0.0373          | 0.9447   | 0.9838        | 0.9866           | 0.9869              | 0.9767        | 0.9878             | 0.9842         | 0.8681   | 0.9819        |
+| 0.026         | 4.2254  | 300  | 0.0254          | 0.9629   | 0.9734        | 0.9912           | 0.9946              | 0.9283        | 0.9973             | 0.9893         | 0.9124   | 0.9871        |
+| 0.0167        | 4.9296  | 350  | 0.0194          | 0.9710   | 0.9832        | 0.9928           | 0.9949              | 0.9589        | 0.9959             | 0.9900         | 0.9331   | 0.9899        |
+| 0.0309        | 5.6338  | 400  | 0.0204          | 0.9705   | 0.9862        | 0.9927           | 0.9935              | 0.9697        | 0.9953             | 0.9899         | 0.9316   | 0.9901        |
+| 0.0129        | 6.3380  | 450  | 0.0187          | 0.9731   | 0.9853        | 0.9932           | 0.9929              | 0.9659        | 0.9972             | 0.9901         | 0.9385   | 0.9906        |
+| 0.0149        | 7.0423  | 500  | 0.0187          | 0.9729   | 0.9872        | 0.9933           | 0.9939              | 0.9718        | 0.9957             | 0.9902         | 0.9375   | 0.9909        |
+| 0.0132        | 7.7465  | 550  | 0.0171          | 0.9746   | 0.9860        | 0.9936           | 0.9948              | 0.9669        | 0.9965             | 0.9910         | 0.9416   | 0.9911        |
+| 0.0149        | 8.4507  | 600  | 0.0178          | 0.9739   | 0.9870        | 0.9935           | 0.9936              | 0.9707        | 0.9965             | 0.9907         | 0.9401   | 0.9910        |
+| 0.0142        | 9.1549  | 650  | 0.0161          | 0.9760   | 0.9900        | 0.9940           | 0.9932              | 0.9805        | 0.9964             | 0.9909         | 0.9450   | 0.9920        |
+| 0.0124        | 9.8592  | 700  | 0.0160          | 0.9768   | 0.9876        | 0.9941           | 0.9946              | 0.9712        | 0.9969             | 0.9913         | 0.9473   | 0.9918        |
+| 0.0077        | 10.5634 | 750  | 0.0170          | 0.9766   | 0.9871        | 0.9942           | 0.9951              | 0.9693        | 0.9969             | 0.9914         | 0.9464   | 0.9920        |
+| 0.0104        | 11.2676 | 800  | 0.0182          | 0.9756   | 0.9857        | 0.9937           | 0.9933              | 0.9661        | 0.9978             | 0.9903         | 0.9452   | 0.9913        |
+| 0.0081        | 11.9718 | 850  | 0.0169          | 0.9759   | 0.9872        | 0.9937           | 0.9924              | 0.9716        | 0.9978             | 0.9903         | 0.9460   | 0.9913        |
+| 0.0108        | 12.6761 | 900  | 0.0167          | 0.9770   | 0.9882        | 0.9942           | 0.9951              | 0.9732        | 0.9963             | 0.9913         | 0.9476   | 0.9919        |
+| 0.0087        | 13.3803 | 950  | 0.0178          | 0.9762   | 0.9867        | 0.9938           | 0.9926              | 0.9695        | 0.9981             | 0.9905         | 0.9469   | 0.9913        |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.19.2
+- Tokenizers 0.19.1

config.json

@@ -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"
+}

model.safetensors

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+oid sha256:fd447ccf12ffc574c6d105ca70ab232a9552555b5d347e4fc891fbd2feee64fc
+size 338531516

training_args.bin

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