BERT

README.md

@@ -1,91 +1,199 @@
 ---
 library_name: transformers
-tags:
-- text-classification
-- sentiment-analysis
-- depression
-- BERT
-- mental-health
-model-index:
-- name: Sentiment Classifier for Depression
-  results:
-  - task:
-      type: text-classification
-    dataset:
-      name: Custom Depression Tweets Dataset
-      type: custom
-    metrics:
-    - name: Accuracy
-      type: accuracy
-      value: 99.87
-    - name: Precision
-      type: precision
-      value: 99.91
-    - name: Recall
-      type: recall
-      value: 99.81
-    - name: F1 Score
-      type: f1
-      value: 99.86
-license: apache-2.0
-language:
-- en
-base_model: google-bert/bert-base-uncased
-metrics:
-- Accuracy
-- Recall
-- Percision
-- F1 Score
-
-widget:
-  - text: "RT EichinChangLim In Talking About Adolescence Book you'll discover key strategies to tackle self-harm panic attacks bullies child"
-    example_title: "Depression"
-  - text: "SharronS Hello there Thanks for reaching out I can understand your frustration I would feel the same Id be happy to take a closer look Please feel free to send me a DM with your full name phone number and email address Lena"
-    example_title: "Non-depression"
-
+tags: []
 ---
 
-# Model Card for Sentiment Classifier for Depression
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+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]
+
+<!-- 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]
+
+### 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]
+
 
-This model is a fine-tuned version of BERT (`bert-base-uncased`) for classifying text as either **Depression** or **Non-depression**. The model was trained on a custom dataset of mental health-related social media posts and has shown high accuracy in sentiment classification.
+#### Training Hyperparameters
 
-## Training Data
-The model was trained on a custom dataset of tweets labeled as either depression-related or not. Data pre-processing included tokenization and removal of special characters.
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
 
-## Training Procedure
-The model was trained using Hugging Face's `transformers` library. The training was conducted on a T4 GPU over 3 epochs, with a batch size of 16 and a learning rate of 5e-5.
+#### Speeds, Sizes, Times [optional]
 
-## Evaluation and Testing Data
-The model was evaluated on a 20% holdout set from the custom dataset.
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
 
-## Results
+[More Information Needed]
 
-- **Accuracy:** 99.87%
-- **Precision:** 99.91%
-- **Recall:** 99.81%
-- **F1 Score:** 99.86%
+## 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
-The carbon emissions from training this model 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:** T4 GPU
-- **Hours used:** 1 hour
-- **Cloud Provider:** Google Cloud (Colab)
-- **Carbon Emitted:** Estimated at 0.45 kg CO2eq
+<!-- 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
+## Technical Specifications [optional]
 
-- **Architecture**: BERT (`bert-base-uncased`)
-- **Training Hardware**: T4 GPU in Colab
-- **Training Library**: Hugging Face `transformers`
+### Model Architecture and Objective
 
-## Citation
+[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:**
-```bibtex
-@misc{poudel2024sentimentclassifier,
-  author = {Poudel, Ashish},
-  title = {Sentiment Classifier for Depression},
-  year = {2024},
-  url = {https://huggingface.co/poudel/sentiment-classifier},
-}
+
+[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]