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Saad287
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segformerSAAD2

Image Segmentation
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Safetensors
segformer
vision
Generated from Trainer
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  1. README.md +114 -196
  2. config.json +80 -0
  3. model.safetensors +3 -0
  4. runs/Aug22_12-52-02_3c74641ca582/events.out.tfevents.1724331135.3c74641ca582.1059.0 +3 -0
  5. 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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-
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- ## Model Details
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-
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- ### Model Description
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-
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- <!-- Provide a longer summary of what this model is. -->
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-
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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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-
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [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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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [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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-
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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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-
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- [More Information Needed]
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-
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- ### Downstream Use [optional]
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-
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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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-
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- [More Information Needed]
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-
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- ### Out-of-Scope Use
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-
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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-
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- [More Information Needed]
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-
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- ## Bias, Risks, and Limitations
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-
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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-
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- [More Information Needed]
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-
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- ### Recommendations
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-
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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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-
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- ## How to Get Started with the Model
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-
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- Use the code below to get started with the model.
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-
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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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-
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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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-
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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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- <!-- 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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-
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- #### Preprocessing [optional]
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-
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- [More Information Needed]
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-
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- #### Training Hyperparameters
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-
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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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-
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- #### Speeds, Sizes, Times [optional]
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-
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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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-
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- ## Evaluation
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-
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- <!-- This section describes the evaluation protocols and provides the results. -->
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-
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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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-
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- #### Factors
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-
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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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-
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- #### Metrics
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-
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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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- [More Information Needed]
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-
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- #### Summary
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-
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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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-
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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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-
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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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-
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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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-
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- ## Technical Specifications [optional]
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-
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- ### Model Architecture and Objective
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- [More Information Needed]
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-
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- ### Compute Infrastructure
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- [More Information Needed]
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-
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- #### Hardware
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- [More Information Needed]
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- #### Software
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- ## Citation [optional]
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-
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- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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- **BibTeX:**
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- [More Information Needed]
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- **APA:**
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- [More Information Needed]
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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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- [More Information Needed]
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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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+ 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: segformerSAAD2
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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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+ # segformerSAAD2
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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 Saad287/SixGUN dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0658
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+ - Mean Iou: 0.8885
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+ - Mean Accuracy: 0.9302
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+ - Overall Accuracy: 0.9934
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+ - Accuracy Bkg: 0.9977
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+ - Accuracy Knife: 0.8700
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+ - Accuracy Gun: 0.9228
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+ - Iou Bkg: 0.9940
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+ - Iou Knife: 0.8345
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+ - Iou Gun: 0.8370
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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: 23
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+ - eval_batch_size: 23
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 500
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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 Bkg | Accuracy Knife | Accuracy Gun | Iou Bkg | Iou Knife | Iou Gun |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------:|:--------------:|:------------:|:-------:|:---------:|:-------:|
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+ | 0.9085 | 10.0 | 10 | 1.0050 | 0.5155 | 0.9279 | 0.9160 | 0.9152 | 0.9126 | 0.9559 | 0.9144 | 0.3135 | 0.3185 |
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+ | 0.7013 | 20.0 | 20 | 0.8010 | 0.6030 | 0.8080 | 0.9590 | 0.9692 | 0.6715 | 0.7832 | 0.9590 | 0.4442 | 0.4060 |
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+ | 0.5991 | 30.0 | 30 | 0.6384 | 0.6286 | 0.7939 | 0.9648 | 0.9765 | 0.6946 | 0.7107 | 0.9647 | 0.5156 | 0.4054 |
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+ | 0.5105 | 40.0 | 40 | 0.5393 | 0.6328 | 0.8246 | 0.9632 | 0.9727 | 0.7618 | 0.7393 | 0.9631 | 0.5383 | 0.3970 |
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+ | 0.4642 | 50.0 | 50 | 0.4625 | 0.6478 | 0.8186 | 0.9668 | 0.9769 | 0.7866 | 0.6922 | 0.9666 | 0.5662 | 0.4108 |
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+ | 0.4301 | 60.0 | 60 | 0.4175 | 0.6580 | 0.8092 | 0.9696 | 0.9805 | 0.7819 | 0.6650 | 0.9693 | 0.5757 | 0.4291 |
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+ | 0.3623 | 70.0 | 70 | 0.3713 | 0.7008 | 0.8249 | 0.9758 | 0.9861 | 0.7827 | 0.7061 | 0.9757 | 0.6257 | 0.5010 |
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+ | 0.3356 | 80.0 | 80 | 0.3247 | 0.7648 | 0.8740 | 0.9825 | 0.9899 | 0.8066 | 0.8254 | 0.9827 | 0.6695 | 0.6422 |
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+ | 0.2975 | 90.0 | 90 | 0.2862 | 0.7936 | 0.8754 | 0.9857 | 0.9932 | 0.8001 | 0.8330 | 0.9860 | 0.6986 | 0.6962 |
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+ | 0.2722 | 100.0 | 100 | 0.2656 | 0.8099 | 0.8962 | 0.9869 | 0.9931 | 0.8202 | 0.8753 | 0.9873 | 0.7126 | 0.7296 |
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+ | 0.2465 | 110.0 | 110 | 0.2377 | 0.8192 | 0.8904 | 0.9880 | 0.9946 | 0.8170 | 0.8597 | 0.9884 | 0.7251 | 0.7440 |
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+ | 0.2221 | 120.0 | 120 | 0.2163 | 0.8311 | 0.9018 | 0.9889 | 0.9949 | 0.8265 | 0.8840 | 0.9895 | 0.7391 | 0.7648 |
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+ | 0.2082 | 130.0 | 130 | 0.2007 | 0.8341 | 0.8971 | 0.9892 | 0.9955 | 0.8297 | 0.8662 | 0.9896 | 0.7500 | 0.7628 |
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+ | 0.1974 | 140.0 | 140 | 0.1928 | 0.8462 | 0.9026 | 0.9901 | 0.9961 | 0.8390 | 0.8729 | 0.9906 | 0.7685 | 0.7795 |
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+ | 0.1823 | 150.0 | 150 | 0.1720 | 0.8464 | 0.8974 | 0.9903 | 0.9966 | 0.8324 | 0.8632 | 0.9907 | 0.7710 | 0.7775 |
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+ | 0.1743 | 160.0 | 160 | 0.1598 | 0.8533 | 0.9014 | 0.9908 | 0.9969 | 0.8307 | 0.8766 | 0.9913 | 0.7799 | 0.7888 |
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+ | 0.1577 | 170.0 | 170 | 0.1560 | 0.8592 | 0.9150 | 0.9911 | 0.9963 | 0.8514 | 0.8973 | 0.9917 | 0.7892 | 0.7967 |
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+ | 0.1468 | 180.0 | 180 | 0.1432 | 0.8632 | 0.9079 | 0.9915 | 0.9972 | 0.8406 | 0.8858 | 0.9920 | 0.7964 | 0.8012 |
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+ | 0.1397 | 190.0 | 190 | 0.1323 | 0.8641 | 0.9128 | 0.9915 | 0.9969 | 0.8503 | 0.8911 | 0.9920 | 0.7993 | 0.8009 |
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+ | 0.1305 | 200.0 | 200 | 0.1264 | 0.8659 | 0.9102 | 0.9917 | 0.9972 | 0.8468 | 0.8867 | 0.9922 | 0.8024 | 0.8032 |
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+ | 0.1228 | 210.0 | 210 | 0.1209 | 0.8730 | 0.9188 | 0.9922 | 0.9972 | 0.8552 | 0.9038 | 0.9927 | 0.8119 | 0.8144 |
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+ | 0.1179 | 220.0 | 220 | 0.1123 | 0.8730 | 0.9172 | 0.9922 | 0.9973 | 0.8527 | 0.9016 | 0.9928 | 0.8128 | 0.8133 |
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+ | 0.1126 | 230.0 | 230 | 0.1078 | 0.8742 | 0.9203 | 0.9923 | 0.9972 | 0.8568 | 0.9069 | 0.9929 | 0.8148 | 0.8149 |
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+ | 0.1066 | 240.0 | 240 | 0.1029 | 0.8758 | 0.9216 | 0.9924 | 0.9972 | 0.8587 | 0.9090 | 0.9930 | 0.8176 | 0.8169 |
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+ | 0.1026 | 250.0 | 250 | 0.0978 | 0.8786 | 0.9224 | 0.9926 | 0.9974 | 0.8648 | 0.9050 | 0.9931 | 0.8230 | 0.8197 |
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+ | 0.1012 | 260.0 | 260 | 0.0963 | 0.8797 | 0.9271 | 0.9927 | 0.9972 | 0.8659 | 0.9182 | 0.9933 | 0.8242 | 0.8217 |
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+ | 0.0952 | 270.0 | 270 | 0.0926 | 0.8800 | 0.9229 | 0.9927 | 0.9975 | 0.8607 | 0.9104 | 0.9933 | 0.8250 | 0.8218 |
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+ | 0.0938 | 280.0 | 280 | 0.0895 | 0.8819 | 0.9238 | 0.9929 | 0.9975 | 0.8649 | 0.9090 | 0.9934 | 0.8284 | 0.8237 |
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+ | 0.0893 | 290.0 | 290 | 0.0860 | 0.8832 | 0.9260 | 0.9930 | 0.9975 | 0.8686 | 0.9120 | 0.9935 | 0.8301 | 0.8261 |
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+ | 0.0868 | 300.0 | 300 | 0.0835 | 0.8831 | 0.9243 | 0.9930 | 0.9976 | 0.8646 | 0.9106 | 0.9935 | 0.8301 | 0.8257 |
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+ | 0.0853 | 310.0 | 310 | 0.0820 | 0.8834 | 0.9257 | 0.9930 | 0.9975 | 0.8664 | 0.9132 | 0.9936 | 0.8307 | 0.8260 |
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+ | 0.0817 | 320.0 | 320 | 0.0786 | 0.8867 | 0.9291 | 0.9932 | 0.9976 | 0.8707 | 0.9190 | 0.9938 | 0.8343 | 0.8319 |
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+ | 0.0823 | 330.0 | 330 | 0.0785 | 0.8851 | 0.9261 | 0.9931 | 0.9977 | 0.8677 | 0.9129 | 0.9937 | 0.8326 | 0.8291 |
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+ | 0.0858 | 340.0 | 340 | 0.0768 | 0.8860 | 0.9272 | 0.9932 | 0.9976 | 0.8680 | 0.9159 | 0.9938 | 0.8330 | 0.8312 |
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+ | 0.078 | 350.0 | 350 | 0.0744 | 0.8853 | 0.9253 | 0.9931 | 0.9977 | 0.8648 | 0.9133 | 0.9937 | 0.8315 | 0.8308 |
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+ | 0.0755 | 360.0 | 360 | 0.0739 | 0.8872 | 0.9290 | 0.9933 | 0.9976 | 0.8694 | 0.9201 | 0.9939 | 0.8337 | 0.8342 |
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+ | 0.0752 | 370.0 | 370 | 0.0727 | 0.8880 | 0.9307 | 0.9933 | 0.9976 | 0.8721 | 0.9224 | 0.9939 | 0.8351 | 0.8349 |
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+ | 0.0727 | 380.0 | 380 | 0.0719 | 0.8858 | 0.9269 | 0.9932 | 0.9977 | 0.8665 | 0.9166 | 0.9938 | 0.8318 | 0.8318 |
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+ | 0.0725 | 390.0 | 390 | 0.0709 | 0.8873 | 0.9298 | 0.9933 | 0.9976 | 0.8705 | 0.9215 | 0.9939 | 0.8347 | 0.8333 |
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+ | 0.0725 | 400.0 | 400 | 0.0695 | 0.8870 | 0.9283 | 0.9933 | 0.9977 | 0.8686 | 0.9188 | 0.9939 | 0.8331 | 0.8340 |
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+ | 0.0718 | 410.0 | 410 | 0.0689 | 0.8890 | 0.9309 | 0.9934 | 0.9976 | 0.8706 | 0.9244 | 0.9940 | 0.8351 | 0.8378 |
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+ | 0.0695 | 420.0 | 420 | 0.0679 | 0.8872 | 0.9284 | 0.9933 | 0.9977 | 0.8689 | 0.9186 | 0.9939 | 0.8335 | 0.8341 |
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+ | 0.0707 | 430.0 | 430 | 0.0676 | 0.8881 | 0.9307 | 0.9933 | 0.9976 | 0.8686 | 0.9258 | 0.9940 | 0.8334 | 0.8370 |
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+ | 0.0684 | 440.0 | 440 | 0.0668 | 0.8883 | 0.9298 | 0.9934 | 0.9977 | 0.8693 | 0.9225 | 0.9940 | 0.8339 | 0.8372 |
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+ | 0.0692 | 450.0 | 450 | 0.0668 | 0.8887 | 0.9310 | 0.9934 | 0.9976 | 0.8708 | 0.9245 | 0.9940 | 0.8350 | 0.8372 |
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+ | 0.0681 | 460.0 | 460 | 0.0661 | 0.8889 | 0.9296 | 0.9934 | 0.9977 | 0.8696 | 0.9216 | 0.9940 | 0.8344 | 0.8382 |
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+ | 0.0688 | 470.0 | 470 | 0.0661 | 0.8888 | 0.9305 | 0.9934 | 0.9977 | 0.8708 | 0.9230 | 0.9940 | 0.8352 | 0.8372 |
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+ | 0.0675 | 480.0 | 480 | 0.0659 | 0.8888 | 0.9307 | 0.9934 | 0.9976 | 0.8717 | 0.9228 | 0.9940 | 0.8353 | 0.8370 |
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+ | 0.0679 | 490.0 | 490 | 0.0659 | 0.8886 | 0.9300 | 0.9934 | 0.9977 | 0.8708 | 0.9214 | 0.9940 | 0.8352 | 0.8367 |
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+ | 0.0668 | 500.0 | 500 | 0.0658 | 0.8885 | 0.9302 | 0.9934 | 0.9977 | 0.8700 | 0.9228 | 0.9940 | 0.8345 | 0.8370 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.4
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.21.0
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+ - Tokenizers 0.19.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "_name_or_path": "nvidia/mit-b0",
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+ "architectures": [
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+ "id2label": {
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+ "Gun": 2,
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+ "model_type": "segformer",
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+ "num_channels": 3,
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+ "patch_sizes": [
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+ "reshape_last_stage": true,
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+ ],
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.42.4"
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+ }
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