Update README.md

README.md

@@ -1,12 +1,29 @@
 ---
 library_name: transformers
-tags: []
+tags:
+- open data ma
+- questions
+- intents
+- classification
+- function calling
+license: apache-2.0
+language:
+- fr
+metrics:
+- accuracy
+pipeline_tag: text-classification
+datasets:
+- tferhan/Data_Gov_Ma_FAQ
+base_model: almanach/camembert-base
 ---
 
 # Model Card for Model ID
 
 <!-- Provide a quick summary of what the model is/does. -->
-
+This model is fine-tuned from the `camembert-base` model and is designed to classify user intent
+questions for the website data.gov.ma in French. It can distinguish whether a user is making a general inquiry
+or requesting specific data. The training data was generated using GPT-4o-mini and includes information specific
+to data.gov.ma. The model was fine-tuned using LoRA with specific hyperparameters, achieving an accuracy of up to 0.98.
 
 
 ## Model Details
@@ -15,185 +32,96 @@ tags: []
 
 <!-- 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]
+- **Developed by:** TFERHAN
+- **Language:** French
+- **License:** Apache 2.0
+- **Finetuned from model:** camembert-base
 
-<!-- Provide the basic links for the model. -->
+## Use Case
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Purpose:** Classify user intent questions for the chatbot on the data.gov.ma website.
+- **Languages:** French (optimized for), performs poorly on other languages.
+- **Data Source:** Generated using GPT-4o-mini with data from data.gov.ma.
 
 ## 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]
+The model can be directly used to classify user intents in chatbot scenarios for the website data.gov.ma, distinguishing between general inquiries and data requests.
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+### Downstream Use
 
-[More Information Needed]
+The model is particularly suited for applications involving the French language and can be integrated into larger chatbot systems or
+fine-tuned further for similar tasks in different contexts.
 
 ### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
+- Misuse for different languages without fine-tuning.
+- Applications that do not involve French language queries.
+- Sensitive or highly critical applications without extensive validation.
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+### Technical Limitations
 
-[More Information Needed]
+- Performance may degrade significantly on languages other than French.
+- Limited to intents related to general queries and data requests.
 
 ### 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.
+- The model should be retrained or fine-tuned with appropriate data before deployment in non-French contexts.
+- Continuous monitoring and evaluation should be conducted to ensure reliability and fairness.
 
 ## How to Get Started with the Model
 
-Use the code below to get started with the model.
+Use the code snippet below to get started with the model:
 
-[More Information Needed]
+```python
+from transformers import pipeline
 
-## Training Details
 
-### Training Data
+model_name = "tferhan/finetuned_camb_intents"
 
-<!-- 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. -->
+nlp_pipeline = pipeline("text-classification", model_name)
 
-[More Information Needed]
+questions = ["qu'est ce que open data", "je veux les informations de l'eau potable"]
+results = nlp_pipeline_class(questions)
 
-### 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]
+for result in results:
+    print(result)
 
+#{'label': 'LABEL_0', 'score': 0.9999700784683228} === general
+#{'label': 'LABEL_1', 'score': 0.9994990825653076} === request_data
+```
 
-#### Training Hyperparameters
+## Training Details
 
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+### Training Data
 
-#### Speeds, Sizes, Times [optional]
+- **Data Source:** Generated using GPT-4o-mini with help from words and data from data.gov.ma.
 
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+### Training Procedure
 
-[More Information Needed]
+- **Preprocessing:** 
+  - Standard text preprocessing steps - tokenization, text cleaning, and normalization.
+- **Training Hyperparameters:**
+  - Epochs: `10`
+  - Train Batch Size: `4`
+  - Eval Batch Size: `4`
+  - Learning Rate: `2e-5`
+  - Evaluation Strategy: `epoch`
+  - Weight Decay: `0.01`
+- **Log History:** `log_history.json`
 
 ## Evaluation
 
-<!-- This section describes the evaluation protocols and provides the results. -->
+### Testing Data & Metrics
 
-### 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]
+- **Testing Data:** Subset of the generated data based on data.gov.ma.
+- **Evaluation Metrics:** Accuracy.
 
 ### Results
 
-[More Information Needed]
-
-#### Summary
-
-
-
-## 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]
-
-## 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]
-
-## Model Card Contact
-
-[More Information Needed]
+- **Maximum Accuracy:** 0.98%