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Patnev71
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segformer-b0-finetuned-floorplan

Image Segmentation
Transformers
Safetensors
segformer
vision
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +169 -195
  2. config.json +78 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md CHANGED
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  ---
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  library_name: transformers
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- tags: []
 
 
 
 
 
 
 
 
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  ---
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- # Model Card for Model ID
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-
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- <!-- Provide a quick summary of what the model is/does. -->
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-
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- ## Model Details
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-
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- ### Model Description
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- <!-- Provide a longer summary of what this model is. -->
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- 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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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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- ### Model Sources [optional]
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- - **Repository:** [More Information Needed]
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-
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- ## Uses
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-
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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-
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- ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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-
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- ### Downstream Use [optional]
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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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- [More Information Needed]
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- ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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- [More Information Needed]
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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- ### Recommendations
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- <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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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.
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- ## How to Get Started with the Model
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- Use the code below to get started with the model.
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- [More Information Needed]
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-
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- ## Training Details
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-
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- ### Training Data
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- <!-- 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. -->
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- [More Information Needed]
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- ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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- #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- [More Information Needed]
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- ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- <!-- This should link to a Dataset Card if possible. -->
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- [More Information Needed]
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- #### Factors
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- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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- [More Information Needed]
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- #### Metrics
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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- [More Information Needed]
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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- <!-- Relevant interpretability work for the model goes here -->
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- [More Information Needed]
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- ## Environmental Impact
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- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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- 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).
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- - **Hardware Type:** [More Information Needed]
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- - **Hours used:** [More Information Needed]
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- - **Cloud Provider:** [More Information Needed]
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- - **Compute Region:** [More Information Needed]
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- - **Carbon Emitted:** [More Information Needed]
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- [More Information Needed]
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- ### Compute Infrastructure
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- #### Hardware
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- #### Software
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- ## Citation [optional]
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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- [More Information Needed]
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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
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- [More Information Needed]
 
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  ---
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  library_name: transformers
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+ license: other
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+ base_model: nvidia/mit-b0
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+ tags:
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+ - vision
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+ - image-segmentation
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+ - generated_from_trainer
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+ model-index:
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+ - name: segformer-b0-finetuned-floorplan
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+ results: []
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  ---
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # segformer-b0-finetuned-floorplan
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+
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+ This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the patnev71/floorplan dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0034
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+ - Mean Iou: 0.0
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+ - Mean Accuracy: nan
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+ - Overall Accuracy: nan
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+ - Accuracy Background: nan
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+ - Accuracy Room: nan
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+ - Iou Background: 0.0
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+ - Iou Room: 0.0
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 6e-05
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 50
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Room | Iou Background | Iou Room |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-------------:|:--------------:|:--------:|
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+ | 0.4537 | 0.4651 | 20 | 0.5128 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.2352 | 0.9302 | 40 | 0.3004 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.215 | 1.3953 | 60 | 0.1865 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.149 | 1.8605 | 80 | 0.1596 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.1142 | 2.3256 | 100 | 0.1121 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0981 | 2.7907 | 120 | 0.0978 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.09 | 3.2558 | 140 | 0.0726 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0631 | 3.7209 | 160 | 0.0562 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0558 | 4.1860 | 180 | 0.0542 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0446 | 4.6512 | 200 | 0.0439 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0481 | 5.1163 | 220 | 0.0397 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0323 | 5.5814 | 240 | 0.0398 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0323 | 6.0465 | 260 | 0.0302 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0235 | 6.5116 | 280 | 0.0352 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.024 | 6.9767 | 300 | 0.0331 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0211 | 7.4419 | 320 | 0.0258 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0193 | 7.9070 | 340 | 0.0202 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0198 | 8.3721 | 360 | 0.0194 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0185 | 8.8372 | 380 | 0.0219 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0209 | 9.3023 | 400 | 0.0188 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.014 | 9.7674 | 420 | 0.0187 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0124 | 10.2326 | 440 | 0.0165 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0125 | 10.6977 | 460 | 0.0141 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0117 | 11.1628 | 480 | 0.0157 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0139 | 11.6279 | 500 | 0.0124 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0111 | 12.0930 | 520 | 0.0151 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0121 | 12.5581 | 540 | 0.0132 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.008 | 13.0233 | 560 | 0.0116 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0097 | 13.4884 | 580 | 0.0127 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0122 | 13.9535 | 600 | 0.0116 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0063 | 14.4186 | 620 | 0.0118 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0096 | 14.8837 | 640 | 0.0102 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0094 | 15.3488 | 660 | 0.0111 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0073 | 15.8140 | 680 | 0.0100 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0062 | 16.2791 | 700 | 0.0103 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0051 | 16.7442 | 720 | 0.0085 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0055 | 17.2093 | 740 | 0.0097 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0074 | 17.6744 | 760 | 0.0107 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0067 | 18.1395 | 780 | 0.0073 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.005 | 18.6047 | 800 | 0.0076 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0049 | 19.0698 | 820 | 0.0086 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0044 | 19.5349 | 840 | 0.0064 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0052 | 20.0 | 860 | 0.0076 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0055 | 20.4651 | 880 | 0.0072 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0075 | 20.9302 | 900 | 0.0089 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0049 | 21.3953 | 920 | 0.0061 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0057 | 21.8605 | 940 | 0.0074 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0042 | 22.3256 | 960 | 0.0066 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0038 | 22.7907 | 980 | 0.0073 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0049 | 23.2558 | 1000 | 0.0061 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0039 | 23.7209 | 1020 | 0.0042 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0037 | 24.1860 | 1040 | 0.0053 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0032 | 24.6512 | 1060 | 0.0063 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0034 | 25.1163 | 1080 | 0.0060 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0032 | 25.5814 | 1100 | 0.0063 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0047 | 26.0465 | 1120 | 0.0061 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.003 | 26.5116 | 1140 | 0.0061 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0027 | 26.9767 | 1160 | 0.0058 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0025 | 27.4419 | 1180 | 0.0061 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0053 | 27.9070 | 1200 | 0.0054 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0039 | 28.3721 | 1220 | 0.0069 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0025 | 28.8372 | 1240 | 0.0062 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0026 | 29.3023 | 1260 | 0.0044 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0028 | 29.7674 | 1280 | 0.0063 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0022 | 30.2326 | 1300 | 0.0061 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0028 | 30.6977 | 1320 | 0.0054 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0025 | 31.1628 | 1340 | 0.0052 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0034 | 31.6279 | 1360 | 0.0056 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0029 | 32.0930 | 1380 | 0.0054 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0024 | 32.5581 | 1400 | 0.0050 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0028 | 33.0233 | 1420 | 0.0051 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0022 | 33.4884 | 1440 | 0.0054 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0022 | 33.9535 | 1460 | 0.0033 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0032 | 34.4186 | 1480 | 0.0038 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0029 | 34.8837 | 1500 | 0.0042 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0019 | 35.3488 | 1520 | 0.0042 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0025 | 35.8140 | 1540 | 0.0042 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.003 | 36.2791 | 1560 | 0.0035 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0023 | 36.7442 | 1580 | 0.0041 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.002 | 37.2093 | 1600 | 0.0038 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0022 | 37.6744 | 1620 | 0.0043 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0027 | 38.1395 | 1640 | 0.0034 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0019 | 38.6047 | 1660 | 0.0034 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0025 | 39.0698 | 1680 | 0.0033 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0019 | 39.5349 | 1700 | 0.0039 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0022 | 40.0 | 1720 | 0.0036 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0015 | 40.4651 | 1740 | 0.0037 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0025 | 40.9302 | 1760 | 0.0039 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0022 | 41.3953 | 1780 | 0.0040 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0018 | 41.8605 | 1800 | 0.0036 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0019 | 42.3256 | 1820 | 0.0031 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0028 | 42.7907 | 1840 | 0.0035 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0022 | 43.2558 | 1860 | 0.0035 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0015 | 43.7209 | 1880 | 0.0030 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.002 | 44.1860 | 1900 | 0.0030 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0018 | 44.6512 | 1920 | 0.0031 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0017 | 45.1163 | 1940 | 0.0034 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0025 | 45.5814 | 1960 | 0.0037 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0019 | 46.0465 | 1980 | 0.0039 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0016 | 46.5116 | 2000 | 0.0035 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0024 | 46.9767 | 2020 | 0.0037 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0018 | 47.4419 | 2040 | 0.0034 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0032 | 47.9070 | 2060 | 0.0035 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.002 | 48.3721 | 2080 | 0.0034 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0018 | 48.8372 | 2100 | 0.0037 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.002 | 49.3023 | 2120 | 0.0035 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+ | 0.0019 | 49.7674 | 2140 | 0.0034 | 0.0 | nan | nan | nan | nan | 0.0 | 0.0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.47.1
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+ - Pytorch 2.5.1+cu121
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
config.json ADDED
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