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_mit-b5_Clean-Set3_Augmented_Medium
+  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_mit-b5_Clean-Set3_Augmented_Medium
+
+This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the Hasano20/Clean-Set3 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0205
+- Mean Iou: 0.9709
+- Mean Accuracy: 0.9837
+- Overall Accuracy: 0.9928
+- Accuracy Background: 0.9979
+- Accuracy Melt: 0.9593
+- Accuracy Substrate: 0.9938
+- Iou Background: 0.9927
+- Iou Melt: 0.9315
+- Iou Substrate: 0.9885
+
+## 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: 0.0002
+- 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: 20
+
+### 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:------------------:|:--------------:|:--------:|:-------------:|
+| 0.1481        | 0.3968 | 50   | 0.1951          | 0.7748   | 0.8972        | 0.9261           | 0.9808              | 0.8114        | 0.8996             | 0.9583         | 0.4859   | 0.8802        |
+| 0.1364        | 0.7937 | 100  | 0.0745          | 0.8855   | 0.9155        | 0.9727           | 0.9933              | 0.7647        | 0.9884             | 0.9753         | 0.7206   | 0.9604        |
+| 0.0776        | 1.1905 | 150  | 0.1238          | 0.8046   | 0.8351        | 0.9565           | 0.9922              | 0.5172        | 0.9960             | 0.9754         | 0.5059   | 0.9325        |
+| 0.0851        | 1.5873 | 200  | 0.0878          | 0.8651   | 0.8901        | 0.9687           | 0.9923              | 0.6841        | 0.9940             | 0.9791         | 0.6665   | 0.9498        |
+| 0.1893        | 1.9841 | 250  | 0.0602          | 0.9077   | 0.9628        | 0.9766           | 0.9958              | 0.9233        | 0.9693             | 0.9872         | 0.7755   | 0.9602        |
+| 0.1236        | 2.3810 | 300  | 0.0643          | 0.9042   | 0.9455        | 0.9768           | 0.9971              | 0.8609        | 0.9783             | 0.9758         | 0.7669   | 0.9699        |
+| 0.0809        | 2.7778 | 350  | 0.0387          | 0.9408   | 0.9699        | 0.9857           | 0.9964              | 0.9271        | 0.9862             | 0.9895         | 0.8562   | 0.9769        |
+| 0.0357        | 3.1746 | 400  | 0.0364          | 0.9431   | 0.9701        | 0.9860           | 0.9948              | 0.9274        | 0.9880             | 0.9897         | 0.8629   | 0.9767        |
+| 0.0408        | 3.5714 | 450  | 0.0424          | 0.9349   | 0.9815        | 0.9834           | 0.9936              | 0.9745        | 0.9765             | 0.9904         | 0.8434   | 0.9708        |
+| 0.0973        | 3.9683 | 500  | 0.0541          | 0.9172   | 0.9798        | 0.9785           | 0.9941              | 0.9796        | 0.9655             | 0.9903         | 0.7997   | 0.9615        |
+| 0.0274        | 4.3651 | 550  | 0.0256          | 0.9636   | 0.9830        | 0.9904           | 0.9967              | 0.9629        | 0.9894             | 0.9893         | 0.9170   | 0.9844        |
+| 0.04          | 4.7619 | 600  | 0.0329          | 0.9482   | 0.9696        | 0.9877           | 0.9977              | 0.9210        | 0.9899             | 0.9888         | 0.8743   | 0.9815        |
+| 0.0301        | 5.1587 | 650  | 0.0247          | 0.9609   | 0.9756        | 0.9905           | 0.9975              | 0.9361        | 0.9933             | 0.9917         | 0.9067   | 0.9844        |
+| 0.0137        | 5.5556 | 700  | 0.0214          | 0.9667   | 0.9779        | 0.9919           | 0.9962              | 0.9414        | 0.9962             | 0.9924         | 0.9206   | 0.9870        |
+| 0.019         | 5.9524 | 750  | 0.0243          | 0.9619   | 0.9817        | 0.9907           | 0.9959              | 0.9577        | 0.9915             | 0.9916         | 0.9090   | 0.9851        |
+| 0.021         | 6.3492 | 800  | 0.0200          | 0.9678   | 0.9853        | 0.9920           | 0.9972              | 0.9668        | 0.9917             | 0.9926         | 0.9237   | 0.9871        |
+| 0.0156        | 6.7460 | 850  | 0.0211          | 0.9689   | 0.9813        | 0.9924           | 0.9965              | 0.9520        | 0.9954             | 0.9926         | 0.9259   | 0.9880        |
+| 0.0153        | 7.1429 | 900  | 0.0205          | 0.9685   | 0.9842        | 0.9923           | 0.9970              | 0.9626        | 0.9930             | 0.9930         | 0.9249   | 0.9876        |
+| 0.0125        | 7.5397 | 950  | 0.0205          | 0.9709   | 0.9837        | 0.9928           | 0.9979              | 0.9593        | 0.9938             | 0.9927         | 0.9315   | 0.9885        |
+
+
+### 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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+size 338531516

training_args.bin

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