End of training

README.md

@@ -1,199 +1,93 @@
 ---
-library_name: transformers
-tags: []
+license: other
+base_model: nvidia/mit-b2
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b2-finetuned-segments-SixrayGun8-15-2024
+  results: []
 ---
 
-# 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.
-
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-## Uses
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-## How to Get Started with the Model
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-## Training Details
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-### Training Data
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-### Training Procedure
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-#### Training Hyperparameters
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-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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+<!-- 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-finetuned-segments-SixrayGun8-15-2024
+
+This model is a fine-tuned version of [nvidia/mit-b2](https://huggingface.co/nvidia/mit-b2) on the saad7489/SIXray_Gun dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0404
+- Mean Iou: 0.5806
+- Mean Accuracy: 0.8934
+- Overall Accuracy: 0.8890
+- Accuracy No-label: nan
+- Accuracy Object1: 0.8756
+- Accuracy Object2: 0.9112
+- Accuracy Object3: nan
+- Accuracy Object4: nan
+- Accuracy Object5: nan
+- Accuracy Object6: nan
+- Iou No-label: 0.0
+- Iou Object1: 0.8624
+- Iou Object2: 0.8795
+- Iou Object3: nan
+- Iou Object4: nan
+- Iou Object5: nan
+- Iou Object6: nan
+
+## 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: 6e-05
+- train_batch_size: 20
+- eval_batch_size: 20
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 60
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy No-label | Accuracy Object1 | Accuracy Object2 | Accuracy Object3 | Accuracy Object4 | Accuracy Object5 | Accuracy Object6 | Iou No-label | Iou Object1 | Iou Object2 | Iou Object3 | Iou Object4 | Iou Object5 | Iou Object6 |
+|:-------------:|:-------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-----------------:|:----------------:|:----------------:|:----------------:|:----------------:|:----------------:|:----------------:|:------------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|:-----------:|
+| 0.9839        | 3.3333  | 20   | 1.1748          | 0.2064   | 0.6978        | 0.6660           | nan               | 0.5695           | 0.8261           | nan              | nan              | nan              | nan              | 0.0          | 0.5204      | 0.5115      | 0.0         | nan         | nan         | 0.0         |
+| 0.3693        | 6.6667  | 40   | 0.2452          | 0.4796   | 0.7757        | 0.7861           | nan               | 0.8178           | 0.7336           | nan              | nan              | nan              | nan              | 0.0          | 0.7380      | 0.7007      | nan         | nan         | nan         | nan         |
+| 0.1373        | 10.0    | 60   | 0.1276          | 0.5223   | 0.8244        | 0.8300           | nan               | 0.8471           | 0.8017           | nan              | nan              | nan              | nan              | 0.0          | 0.7908      | 0.7761      | nan         | nan         | nan         | nan         |
+| 0.072         | 13.3333 | 80   | 0.0732          | 0.5281   | 0.8149        | 0.8097           | nan               | 0.7937           | 0.8360           | nan              | nan              | nan              | nan              | 0.0          | 0.7729      | 0.8113      | nan         | nan         | nan         | nan         |
+| 0.0488        | 16.6667 | 100  | 0.0609          | 0.4191   | 0.8643        | 0.8619           | nan               | 0.8546           | 0.8739           | nan              | nan              | nan              | nan              | 0.0          | 0.8313      | 0.8450      | 0.0         | nan         | nan         | nan         |
+| 0.0408        | 20.0    | 120  | 0.0539          | 0.5675   | 0.8731        | 0.8666           | nan               | 0.8468           | 0.8993           | nan              | nan              | nan              | nan              | 0.0          | 0.8358      | 0.8668      | nan         | nan         | nan         | nan         |
+| 0.039         | 23.3333 | 140  | 0.0491          | 0.5618   | 0.8647        | 0.8590           | nan               | 0.8414           | 0.8881           | nan              | nan              | nan              | nan              | 0.0          | 0.8264      | 0.8590      | nan         | nan         | nan         | nan         |
+| 0.0365        | 26.6667 | 160  | 0.0484          | 0.4312   | 0.8834        | 0.8773           | nan               | 0.8588           | 0.9081           | nan              | nan              | nan              | nan              | 0.0          | 0.8494      | 0.8753      | 0.0         | nan         | nan         | nan         |
+| 0.0721        | 30.0    | 180  | 0.0486          | 0.4383   | 0.9014        | 0.8957           | nan               | 0.8783           | 0.9245           | nan              | nan              | nan              | nan              | 0.0          | 0.8673      | 0.8861      | 0.0         | nan         | nan         | nan         |
+| 0.0311        | 33.3333 | 200  | 0.0446          | 0.5701   | 0.8758        | 0.8697           | nan               | 0.8509           | 0.9007           | nan              | nan              | nan              | nan              | 0.0          | 0.8400      | 0.8704      | nan         | nan         | nan         | nan         |
+| 0.0404        | 36.6667 | 220  | 0.0431          | 0.5719   | 0.8794        | 0.8748           | nan               | 0.8609           | 0.8978           | nan              | nan              | nan              | nan              | 0.0          | 0.8472      | 0.8686      | nan         | nan         | nan         | nan         |
+| 0.0284        | 40.0    | 240  | 0.0441          | 0.5852   | 0.9034        | 0.8989           | nan               | 0.8852           | 0.9216           | nan              | nan              | nan              | nan              | 0.0          | 0.8701      | 0.8855      | nan         | nan         | nan         | nan         |
+| 0.0302        | 43.3333 | 260  | 0.0424          | 0.4372   | 0.8979        | 0.8935           | nan               | 0.8799           | 0.9159           | nan              | nan              | nan              | nan              | 0.0          | 0.8668      | 0.8819      | 0.0         | nan         | nan         | nan         |
+| 0.0283        | 46.6667 | 280  | 0.0429          | 0.5891   | 0.9094        | 0.9046           | nan               | 0.8899           | 0.9290           | nan              | nan              | nan              | nan              | 0.0          | 0.8762      | 0.8910      | nan         | nan         | nan         | nan         |
+| 0.0261        | 50.0    | 300  | 0.0413          | 0.5813   | 0.8950        | 0.8904           | nan               | 0.8765           | 0.9135           | nan              | nan              | nan              | nan              | 0.0          | 0.8632      | 0.8808      | nan         | nan         | nan         | nan         |
+| 0.023         | 53.3333 | 320  | 0.0404          | 0.5822   | 0.8966        | 0.8910           | nan               | 0.8742           | 0.9190           | nan              | nan              | nan              | nan              | 0.0          | 0.8620      | 0.8845      | nan         | nan         | nan         | nan         |
+| 0.0241        | 56.6667 | 340  | 0.0407          | 0.5848   | 0.9011        | 0.8969           | nan               | 0.8839           | 0.9184           | nan              | nan              | nan              | nan              | 0.0          | 0.8700      | 0.8844      | nan         | nan         | nan         | nan         |
+| 0.0527        | 60.0    | 360  | 0.0404          | 0.5806   | 0.8934        | 0.8890           | nan               | 0.8756           | 0.9112           | nan              | nan              | nan              | nan              | 0.0          | 0.8624      | 0.8795      | nan         | nan         | nan         | nan         |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

config.json

@@ -0,0 +1,88 @@
+{
+  "_name_or_path": "nvidia/mit-b2",
+  "architectures": [
+    "SegformerForSemanticSegmentation"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "decoder_hidden_size": 768,
+  "depths": [
+    3,
+    4,
+    6,
+    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": "no-label",
+    "1": "object1",
+    "2": "object2",
+    "3": "object3",
+    "4": "object4",
+    "5": "object5",
+    "6": "object6"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "no-label": 0,
+    "object1": 1,
+    "object2": 2,
+    "object3": 3,
+    "object4": 4,
+    "object5": 5,
+    "object6": 6
+  },
+  "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": "4.42.4"
+}

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