Update README.md

README.md

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 # Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
+# Convolutional Neural Network (CNN) for CIFAR-10 Dataset
+This repository contains a Convolutional Neural Network (CNN) model trained on the CIFAR-10 dataset. CIFAR-10 is a popular benchmark dataset in the field of computer vision, consisting of 60,000 32x32 color images in 10 classes, with 6,000 images per class.
 
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
+# Model Architecture:
+The CNN model architecture consists of several convolutional layers followed by max-pooling layers, batch normalization, and ReLU activation functions. The final layers typically include one or more fully connected layers followed by a softmax layer for classification.
 
-## Model Details
+# Dataset:
+CIFAR-10 dataset is used for training and evaluation. It comprises 50,000 training images and 10,000 test images across 10 classes, including airplanes, cars, birds, cats, deer, dogs, frogs, horses, ships, and trucks.
 
-### Model Description
+# Training:
+The model is trained using stochastic gradient descent (SGD) or other optimization algorithms with appropriate hyperparameters such as learning rate, batch size, and number of epochs.
 
-<!-- Provide a longer summary of what this model is. -->
+# Evaluation:
+The performance of the model is evaluated using metrics such as accuracy, precision, recall, and F1-score on a separate validation set or through cross-validation.
 
+# Usage:
+The trained model can be used for various computer vision tasks, including image classification, object detection, and image segmentation.
 
-
-- **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]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[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]
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-### 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. -->
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-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### 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 -->
-
-#### 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]
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-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
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-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
+- **Developed by:** Irfan Arshad
+- **Funded by [optional]:** PAF-IAST
+- **Shared by [optional]:** Irfan Arshad
+- **Model type:** Classification Model
+- **Language(s) (NLP):** Python Tensorflow Deep Learning
 
 ### Results
 
-[More Information Needed]
-
-#### Summary
-
-
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-## 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]
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-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
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-### Compute Infrastructure
-
-[More Information Needed]
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-#### Hardware
-
-[More Information Needed]
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/663b152c699810ce7e540fe7/ScWiPc6-xnOraO6aZwnal.png)
 
 #### 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. -->
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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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-[More Information Needed]
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-## Model Card Contact
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-[More Information Needed]
+Google Colab
+Visual Studio Code
+Web Browser