Update README.md

README.md

@@ -1,11 +1,13 @@
 ---
-library_name: transformers
-tags: []
+tags:
+- text-classification  # Change this based on your model type
+pipeline_tag: text-classification  # Choose the correct pipeline
 ---
 
+
 # Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
+This model is designed to classify news articles 
 
 
 
@@ -13,187 +15,118 @@ tags: []
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
+This model is designed to classify news articles from the Daily Mirror Online, a Sri Lankan news source,
+into five categories: Business, Opinion, Political Gossip, Sports, and World News. And this model is developed to analyze and process news content for tasks such as sentiment analysis, or summarization
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
 
-- **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]
+### Data Sources [optional]
 
 <!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+The original dataset contained real news content of Daily Mirror ,  after preprocessing, 1,015 records were selected for training.The data split as %80 train and %20 validation.
 
 ## 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]
+The model can be used for:
+
+Automatic categorization of Sri Lankan news articles
+
+News filtering and recommendation systems
+
+Preliminary analysis of sentiment in news articles
+
 
 ### Downstream Use [optional]
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+News aggregation platforms can use the model to categorize and sort articles.
+
+Journalists and researchers can analyze media trends based on category distributions.
 
-[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]
+This model should not be used for critical decision-making tasks such as political analysis, stock market predictions, or legal judgments.
+
+It may not generalize well to non-Sri Lankan news sources.
+
+
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+The dataset is limited to Daily Mirror Online, which may introduce biases in classification.
+
+The model might misclassify articles if they contain mixed topics.
 
-[More Information Needed]
+The dataset size is small (1,015 articles), which may impact performance on diverse news sources.
 
-### 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]
+```python
+new_model = "Imasha17/News_classification.4"
 
-## Training Details
+# Use a pipeline as a high-level helper
+from transformers import pipeline
 
-### 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]
+pipe = pipeline("text-classification", model="Imasha17/News_classification.4")
+text="Enter your news here"
+pipe (text)
 
-### Training Procedure
+   ```
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+## Training Details
 
-#### Preprocessing [optional]
+### Training Data
 
-[More Information Needed]
+The dataset comprises 1,015 preprocessed news articles from Daily Mirror Online.
 
 
 #### 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. -->
+Model Architecture: distilbert-base-uncased
 
-[More Information Needed]
+Batch Size: 4
 
-## Evaluation
+Epochs: 3
 
-<!-- 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. -->
+20% of the dataset (203 articles) used for validation/testing.
 
-[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
-
+The model performed well, but misclassification occurs when articles have overlapping content.
 
 
 ## Model Examination [optional]
 
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
 
-## Environmental Impact
+The model effectively classifies Sri Lankan news articles.
 
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+It can be fine-tuned on larger datasets for improved accuracy.
 
-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]
+distilbert-base-uncased
 
-## Model Card Contact
+Objective: Multiclass text classification
 
-[More Information Needed]