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.gitignore

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+checkpoint-*/

README.md

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+---
+base_model: ''
+tags:
+- generated_from_trainer
+model-index:
+- name: glacformer
+  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. -->
+
+# glacformer
+
+This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0333
+- Mean Iou: 0.9528
+- Mean Accuracy: 0.9772
+- Overall Accuracy: 0.9885
+- Per Category Iou: [0.9855230058020051, 0.8845759711828091, 0.9883964861024538]
+- Per Category Accuracy: [0.9921669407092866, 0.9462930795421282, 0.9931901963885149]
+
+## 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: 4
+- eval_batch_size: 1
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou                                             | Per Category Accuracy                                        |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------------------------------------------------:|:------------------------------------------------------------:|
+| 0.045         | 1.0   | 523  | 0.0421          | 0.9477   | 0.9795        | 0.9869           | [0.9852157890390353, 0.8719898483736556, 0.9857700613925825] | [0.9904340924248899, 0.9587586082053337, 0.9893900149083925] |
+| 0.0372        | 2.0   | 1046 | 0.0333          | 0.9528   | 0.9772        | 0.9885           | [0.9855230058020051, 0.8845759711828091, 0.9883964861024538] | [0.9921669407092866, 0.9462930795421282, 0.9931901963885149] |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 1.14.0.dev20221130+cu117
+- Datasets 2.13.1
+- Tokenizers 0.13.3

config.json

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+{
+  "architectures": [
+    "SegformerForSemanticSegmentation"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "decoder_hidden_size": 768,
+  "depths": [
+    2,
+    3,
+    4,
+    3
+  ],
+  "drop_path_rate": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_sizes": [
+    64,
+    128,
+    320,
+    512
+  ],
+  "id2label": {
+    "0": "sky",
+    "1": "surface-to-bed",
+    "2": "bed-to-bottom"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "bed-to-bottom": 2,
+    "sky": 0,
+    "surface-to-bed": 1
+  },
+  "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": "4.31.0"
+}

pytorch_model.bin

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training_args.bin

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