End of training

README.md

@@ -1,199 +1,84 @@
 ---
-library_name: transformers
-tags: []
+license: other
+base_model: nvidia/mit-b0
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b0-finetuned-segments-SixrayKnife8-19-2024
+  results: []
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
-
-### Model Description
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-<!-- 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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+<!-- 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-b0-finetuned-segments-SixrayKnife8-19-2024
+
+This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the saad7489/SixraygunTest dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1115
+- Mean Iou: 0.5303
+- Mean Accuracy: 0.8219
+- Overall Accuracy: 0.8241
+- Accuracy No-label: nan
+- Accuracy Object1: 0.7687
+- Accuracy Object2: 0.8750
+- Iou No-label: 0.0
+- Iou Object1: 0.7490
+- Iou Object2: 0.8419
+
+## 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: 2
+- eval_batch_size: 2
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy No-label | Accuracy Object1 | Accuracy Object2 | Iou No-label | Iou Object1 | Iou Object2 |
+|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-----------------:|:----------------:|:----------------:|:------------:|:-----------:|:-----------:|
+| 0.7611        | 0.5714 | 20   | 0.8142          | 0.4605   | 0.7424        | 0.7475           | nan               | 0.6191           | 0.8657           | 0.0          | 0.5843      | 0.7972      |
+| 0.5536        | 1.1429 | 40   | 0.5423          | 0.4213   | 0.6634        | 0.6649           | nan               | 0.6273           | 0.6995           | 0.0          | 0.5901      | 0.6738      |
+| 0.4596        | 1.7143 | 60   | 0.3893          | 0.4241   | 0.6612        | 0.6631           | nan               | 0.6141           | 0.7082           | 0.0          | 0.5917      | 0.6806      |
+| 0.3381        | 2.2857 | 80   | 0.3491          | 0.4801   | 0.7495        | 0.7519           | nan               | 0.6899           | 0.8091           | 0.0          | 0.6667      | 0.7734      |
+| 0.3111        | 2.8571 | 100  | 0.2911          | 0.4866   | 0.7608        | 0.7625           | nan               | 0.7182           | 0.8034           | 0.0          | 0.6903      | 0.7694      |
+| 0.2502        | 3.4286 | 120  | 0.2509          | 0.4867   | 0.7679        | 0.7711           | nan               | 0.6886           | 0.8472           | 0.0          | 0.6721      | 0.7879      |
+| 0.2424        | 4.0    | 140  | 0.2076          | 0.4972   | 0.7723        | 0.7741           | nan               | 0.7279           | 0.8167           | 0.0          | 0.7028      | 0.7887      |
+| 0.1906        | 4.5714 | 160  | 0.2053          | 0.4997   | 0.7763        | 0.7785           | nan               | 0.7231           | 0.8296           | 0.0          | 0.7001      | 0.7992      |
+| 0.1627        | 5.1429 | 180  | 0.1678          | 0.5004   | 0.7767        | 0.7785           | nan               | 0.7309           | 0.8224           | 0.0          | 0.7081      | 0.7932      |
+| 0.1474        | 5.7143 | 200  | 0.1535          | 0.5124   | 0.7966        | 0.7990           | nan               | 0.7395           | 0.8538           | 0.0          | 0.7195      | 0.8177      |
+| 0.1378        | 6.2857 | 220  | 0.1405          | 0.5193   | 0.8060        | 0.8084           | nan               | 0.7477           | 0.8642           | 0.0          | 0.7275      | 0.8302      |
+| 0.1273        | 6.8571 | 240  | 0.1284          | 0.5254   | 0.8160        | 0.8185           | nan               | 0.7554           | 0.8766           | 0.0          | 0.7357      | 0.8405      |
+| 0.1349        | 7.4286 | 260  | 0.1224          | 0.5245   | 0.8130        | 0.8150           | nan               | 0.7645           | 0.8614           | 0.0          | 0.7428      | 0.8307      |
+| 0.1245        | 8.0    | 280  | 0.1178          | 0.5241   | 0.8146        | 0.8174           | nan               | 0.7468           | 0.8824           | 0.0          | 0.7306      | 0.8417      |
+| 0.1183        | 8.5714 | 300  | 0.1105          | 0.5290   | 0.8202        | 0.8223           | nan               | 0.7681           | 0.8722           | 0.0          | 0.7487      | 0.8384      |
+| 0.1124        | 9.1429 | 320  | 0.1092          | 0.5302   | 0.8222        | 0.8246           | nan               | 0.7653           | 0.8791           | 0.0          | 0.7469      | 0.8438      |
+| 0.1102        | 9.7143 | 340  | 0.1115          | 0.5303   | 0.8219        | 0.8241           | nan               | 0.7687           | 0.8750           | 0.0          | 0.7490      | 0.8419      |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

config.json

@@ -0,0 +1,80 @@
+{
+  "_name_or_path": "nvidia/mit-b0",
+  "architectures": [
+    "SegformerForSemanticSegmentation"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "decoder_hidden_size": 256,
+  "depths": [
+    2,
+    2,
+    2,
+    2
+  ],
+  "downsampling_rates": [
+    1,
+    4,
+    8,
+    16
+  ],
+  "drop_path_rate": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_sizes": [
+    32,
+    64,
+    160,
+    256
+  ],
+  "id2label": {
+    "0": "no-label",
+    "1": "object1",
+    "2": "object2"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "no-label": 0,
+    "object1": 1,
+    "object2": 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": "4.42.4"
+}

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training_args.bin

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