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README.md +86 -196
config.json +90 -0
model.safetensors +3 -0
training_args.bin +3 -0

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 ---
-library_name: transformers
-tags: []
 ---
-# 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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-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-## How to Get Started with the Model
-Use the code below to get started with the model.
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-## Training Details
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 ---
+license: other
+base_model: sayeed99/segformer-b3-fashion
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b3-fashion-finetuned-polo-segments-v1.4
+  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-b3-fashion-finetuned-polo-segments-v1.4
+This model is a fine-tuned version of [sayeed99/segformer-b3-fashion](https://huggingface.co/sayeed99/segformer-b3-fashion) on the sshk/polo-badges-segmentation dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0547
+- Mean Iou: 0.7482
+- Mean Accuracy: 0.9206
+- Overall Accuracy: 0.9823
+- Accuracy Unlabeled: nan
+- Accuracy Collar: 0.8807
+- Accuracy Polo: 0.9847
+- Accuracy Lines-cuff: 0.7598
+- Accuracy Lines-chest: 0.9230
+- Accuracy Human: 0.9823
+- Accuracy Background: 0.9929
+- Accuracy Tape: nan
+- Iou Unlabeled: nan
+- Iou Collar: 0.8276
+- Iou Polo: 0.9580
+- Iou Lines-cuff: 0.6735
+- Iou Lines-chest: 0.8230
+- Iou Human: 0.9680
+- Iou Background: 0.9872
+- Iou Tape: 0.0
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 30
+### Training results
+| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Collar | Accuracy Polo | Accuracy Lines-cuff | Accuracy Lines-chest | Accuracy Human | Accuracy Background | Accuracy Tape | Iou Unlabeled | Iou Collar | Iou Polo | Iou Lines-cuff | Iou Lines-chest | Iou Human | Iou Background | Iou Tape |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:---------------:|:-------------:|:-------------------:|:--------------------:|:--------------:|:-------------------:|:-------------:|:-------------:|:----------:|:--------:|:--------------:|:---------------:|:---------:|:--------------:|:--------:|
+| 0.206         | 2.5   | 20   | 0.1808          | 0.5772   | 0.6083        | 0.9552           | nan                | 0.6933          | 0.9875        | 0.0                 | 0.0304               | 0.9818         | 0.9566              | nan           | nan           | 0.6406     | 0.9100   | 0.0            | 0.0276          | 0.9299    | 0.9553         | nan      |
+| 0.0873        | 5.0   | 40   | 0.0882          | 0.7806   | 0.8207        | 0.9768           | nan                | 0.8457          | 0.9848        | 0.2359              | 0.8896               | 0.9780         | 0.9904              | nan           | nan           | 0.7808     | 0.9460   | 0.2351         | 0.7783          | 0.9605    | 0.9827         | nan      |
+| 0.0648        | 7.5   | 60   | 0.0712          | 0.8502   | 0.8900        | 0.9794           | nan                | 0.8586          | 0.9880        | 0.6659              | 0.8584               | 0.9796         | 0.9892              | nan           | nan           | 0.8059     | 0.9499   | 0.6054         | 0.7918          | 0.9642    | 0.9842         | nan      |
+| 0.0607        | 10.0  | 80   | 0.0631          | 0.8556   | 0.8957        | 0.9806           | nan                | 0.8586          | 0.9856        | 0.7087              | 0.8477               | 0.9829         | 0.9907              | nan           | nan           | 0.8055     | 0.9539   | 0.6394         | 0.7834          | 0.9659    | 0.9856         | nan      |
+| 0.057         | 12.5  | 100  | 0.0605          | 0.8661   | 0.9135        | 0.9815           | nan                | 0.8708          | 0.9818        | 0.7296              | 0.9224               | 0.9855         | 0.9908              | nan           | nan           | 0.8148     | 0.9570   | 0.6577         | 0.8144          | 0.9669    | 0.9859         | nan      |
+| 0.0458        | 15.0  | 120  | 0.0573          | 0.7446   | 0.9169        | 0.9819           | nan                | 0.8925          | 0.9838        | 0.7505              | 0.9009               | 0.9792         | 0.9949              | nan           | nan           | 0.8244     | 0.9581   | 0.6600         | 0.8164          | 0.9669    | 0.9863         | 0.0      |
+| 0.0413        | 17.5  | 140  | 0.0587          | 0.7428   | 0.9196        | 0.9818           | nan                | 0.8818          | 0.9820        | 0.7483              | 0.9299               | 0.9823         | 0.9932              | nan           | nan           | 0.8217     | 0.9571   | 0.6671         | 0.7997          | 0.9673    | 0.9869         | 0.0      |
+| 0.0449        | 20.0  | 160  | 0.0542          | 0.7468   | 0.9202        | 0.9826           | nan                | 0.8850          | 0.9833        | 0.7516              | 0.9248               | 0.9842         | 0.9925              | nan           | nan           | 0.8270     | 0.9590   | 0.6678         | 0.8179          | 0.9688    | 0.9873         | 0.0      |
+| 0.0394        | 22.5  | 180  | 0.0558          | 0.7468   | 0.9208        | 0.9819           | nan                | 0.8934          | 0.9853        | 0.7528              | 0.9207               | 0.9808         | 0.9919              | nan           | nan           | 0.8298     | 0.9564   | 0.6657         | 0.8214          | 0.9672    | 0.9869         | 0.0      |
+| 0.0472        | 25.0  | 200  | 0.0549          | 0.7474   | 0.9185        | 0.9823           | nan                | 0.8792          | 0.9854        | 0.7531              | 0.9186               | 0.9828         | 0.9922              | nan           | nan           | 0.8274     | 0.9577   | 0.6681         | 0.8233          | 0.9681    | 0.9871         | 0.0      |
+| 0.0452        | 27.5  | 220  | 0.0547          | 0.7482   | 0.9217        | 0.9823           | nan                | 0.8837          | 0.9846        | 0.7622              | 0.9247               | 0.9823         | 0.9927              | nan           | nan           | 0.8287     | 0.9580   | 0.6733         | 0.8221          | 0.9681    | 0.9871         | 0.0      |
+| 0.0392        | 30.0  | 240  | 0.0547          | 0.7482   | 0.9206        | 0.9823           | nan                | 0.8807          | 0.9847        | 0.7598              | 0.9230               | 0.9823         | 0.9929              | nan           | nan           | 0.8276     | 0.9580   | 0.6735         | 0.8230          | 0.9680    | 0.9872         | 0.0      |
+### Framework versions
+- Transformers 4.44.0
+- Pytorch 2.4.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json ADDED Viewed

	@@ -0,0 +1,90 @@

+{
+  "_name_or_path": "sayeed99/segformer-b3-fashion",
+  "architectures": [
+    "SegformerForSemanticSegmentation"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "classifier_dropout_prob": 0.1,
+  "decoder_hidden_size": 768,
+  "depths": [
+    3,
+    4,
+    18,
+    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": "unlabeled",
+    "1": "collar",
+    "2": "polo",
+    "3": "lines-cuff",
+    "4": "lines-chest",
+    "5": "human",
+    "6": "background",
+    "7": "tape"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "background": 6,
+    "collar": 1,
+    "human": 5,
+    "lines-chest": 4,
+    "lines-cuff": 3,
+    "polo": 2,
+    "tape": 7,
+    "unlabeled": 0
+  },
+  "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": "4.44.0"
+}

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