End of training

README.md

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+---
+license: other
+base_model: nvidia/mit-b0
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b0-finetuned-segments-pageboundet-finaltry
+  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. -->
+
+# segformer-b0-finetuned-segments-pageboundet-finaltry
+
+This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the vigneshgs7/Boundary_detection_onelasttry dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2569
+- Mean Iou: nan
+- Mean Accuracy: nan
+- Overall Accuracy: nan
+- Accuracy Object: nan
+- Accuracy Surface: nan
+- Iou Object: nan
+- Iou Surface: 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: 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 Object | Accuracy Surface | Iou Object | Iou Surface |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:---------------:|:----------------:|:----------:|:-----------:|
+| 0.4616        | 2.0   | 20   | 0.4828          | nan      | nan           | nan              | nan             | nan              | nan        | nan         |
+| 0.3359        | 4.0   | 40   | 0.3351          | nan      | nan           | nan              | nan             | nan              | nan        | nan         |
+| 0.2898        | 6.0   | 60   | 0.2885          | nan      | nan           | nan              | nan             | nan              | nan        | nan         |
+| 0.3041        | 8.0   | 80   | 0.2671          | nan      | nan           | nan              | nan             | nan              | nan        | nan         |
+| 0.2429        | 10.0  | 100  | 0.2569          | nan      | nan           | nan              | nan             | nan              | nan        | nan         |
+
+
+### Framework versions
+
+- Transformers 4.35.0
+- Pytorch 2.1.0
+- Datasets 2.14.6
+- Tokenizers 0.14.1

config.json

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+{
+  "_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": "object",
+    "1": "surface"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "object": 0,
+    "surface": 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": "4.35.0"
+}

model.safetensors

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runs/Dec17_20-59-40_Vigneshs-MBP.alphionsee.in/events.out.tfevents.1702827017.Vigneshs-MBP.alphionsee.in.72633.0

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training_args.bin

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