End of training

README.md

@@ -1,199 +1,82 @@
 ---
-library_name: transformers
-tags: []
+license: other
+base_model: sayeed99/segformer-b3-fashion
+tags:
+- vision
+- image-segmentation
+- generated_from_trainer
+model-index:
+- name: segformer-b3-fashion-finetuned-polo-segments-aug-07-v1.2
+  results: []
 ---
 
-# Model Card for Model ID
+<!-- 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. -->
 
-<!-- Provide a quick summary of what the model is/does. -->
+# segformer-b3-fashion-finetuned-polo-segments-aug-07-v1.2
 
+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: 0.0582
+- Mean Iou: 0.8583
+- Mean Accuracy: 0.9104
+- Overall Accuracy: 0.9803
+- Accuracy Unlabeled: nan
+- Accuracy Collar: 0.8741
+- Accuracy Polo: 0.9786
+- Accuracy Lines-cuff: 0.7185
+- Accuracy Lines-chest: 0.9188
+- Accuracy Human: 0.9805
+- Accuracy Background: 0.9920
+- Iou Unlabeled: nan
+- Iou Collar: 0.8111
+- Iou Polo: 0.9580
+- Iou Lines-cuff: 0.6290
+- Iou Lines-chest: 0.8101
+- Iou Human: 0.9553
+- Iou Background: 0.9863
 
+## Model description
 
-## Model Details
+More information needed
 
-### Model Description
+## Intended uses & limitations
 
-<!-- Provide a longer summary of what this model is. -->
+More information needed
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+## Training and evaluation data
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+More information needed
 
-### Model Sources [optional]
+## Training procedure
 
-<!-- Provide the basic links for the model. -->
+### Training hyperparameters
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+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
 
-## Uses
+### Training results
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+| 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 | Iou Unlabeled | Iou Collar | Iou Polo | Iou Lines-cuff | Iou Lines-chest | Iou Human | Iou Background |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:---------------:|:-------------:|:-------------------:|:--------------------:|:--------------:|:-------------------:|:-------------:|:----------:|:--------:|:--------------:|:---------------:|:---------:|:--------------:|
+| 0.1564        | 4.0   | 20   | 0.1474          | 0.5073   | 0.6210        | 0.9633           | nan                | 0.7561          | 0.9797        | 0.0183              | 0.0138               | 0.9829         | 0.9750              | 0.0           | 0.6873     | 0.9282   | 0.0182         | 0.0131          | 0.9332    | 0.9714         |
+| 0.0912        | 8.0   | 40   | 0.0812          | 0.7332   | 0.7637        | 0.9751           | nan                | 0.8012          | 0.9798        | 0.1221              | 0.7058               | 0.9886         | 0.9847              | nan           | 0.7652     | 0.9512   | 0.1220         | 0.6314          | 0.9483    | 0.9811         |
+| 0.0724        | 12.0  | 60   | 0.0693          | 0.8345   | 0.8765        | 0.9791           | nan                | 0.8651          | 0.9817        | 0.5794              | 0.8633               | 0.9810         | 0.9888              | nan           | 0.8025     | 0.9570   | 0.5407         | 0.7688          | 0.9537    | 0.9844         |
+| 0.0609        | 16.0  | 80   | 0.0633          | 0.8506   | 0.9022        | 0.9796           | nan                | 0.8697          | 0.9771        | 0.6806              | 0.9123               | 0.9826         | 0.9907              | nan           | 0.8093     | 0.9573   | 0.6053         | 0.7921          | 0.9541    | 0.9853         |
+| 0.0602        | 20.0  | 100  | 0.0629          | 0.8493   | 0.8960        | 0.9794           | nan                | 0.8576          | 0.9789        | 0.6686              | 0.8987               | 0.9818         | 0.9904              | nan           | 0.8024     | 0.9569   | 0.6004         | 0.7974          | 0.9532    | 0.9855         |
+| 0.0536        | 24.0  | 120  | 0.0588          | 0.8556   | 0.9083        | 0.9801           | nan                | 0.8709          | 0.9788        | 0.7104              | 0.9172               | 0.9823         | 0.9902              | nan           | 0.8090     | 0.9581   | 0.6244         | 0.8011          | 0.9552    | 0.9856         |
+| 0.0459        | 28.0  | 140  | 0.0582          | 0.8583   | 0.9104        | 0.9803           | nan                | 0.8741          | 0.9786        | 0.7185              | 0.9188               | 0.9805         | 0.9920              | nan           | 0.8111     | 0.9580   | 0.6290         | 0.8101          | 0.9553    | 0.9863         |
 
-### Direct Use
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+### Framework versions
 
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-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.
-
-[More Information Needed]
-
-## Training Details
-
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-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).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
+- Transformers 4.44.0
+- Pytorch 2.4.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

config.json

@@ -0,0 +1,88 @@
+{
+  "_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"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "label2id": {
+    "background": 6,
+    "collar": 1,
+    "human": 5,
+    "lines-chest": 4,
+    "lines-cuff": 3,
+    "polo": 2,
+    "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"
+}

model.safetensors

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+oid sha256:91ec1e7cd185fdbcc688a5f1b12829720bd4bebc687734c2108492fafd6a61c0
+size 188995156

training_args.bin

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