Update README.md

README.md

@@ -1,199 +1,131 @@
 ---
 library_name: transformers
-tags: []
+language:
+- en
+metrics:
+- bleu
+pipeline_tag: translation
 ---
 
 # Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
-
+Model Card for English-to-Darija Translation (mBART Fine-tuned Model)
 
 
 ## Model Details
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
-
+This model is a fine-tuned version of the facebook/mbart-large-50-many-to-many-mmt model, 
+specifically tailored for translating English text to Moroccan Darija in Arabic script. 
+The model was trained on a custom dataset of English-Darija sentence pairs,
+and it has been designed to accurately capture the nuances of the Moroccan dialect.
 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:** Aicha Lahnouki
+- **Finetuned from model:** facebook/mbart-large-50-many-to-many-mmt
+- **Model type:** Sequence-to-Sequence Translation (mBART architecture)
+- **Language(s) (NLP):** English (en_XX), Darija (ar_AR)
 
-<!-- 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]
+This model is intended for translating English sentences into Moroccan Darija in Arabic script. 
+It can be used in applications such as translation services, language learning tools, or chatbots.
 
-### 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. -->
+This model was trained on 50% of the dataset provided by DODa, consisting of 45,000 rows. 
+The testing was conducted on a sample of 100 sentences. Due to the reduced training data, 
+the model might not capture the full linguistic diversity of English-to-Darija translations. 
+Additionally, the limited test size may not fully represent the model's performance across all possible inputs,
+leading to potential biases or inaccuracies when applied to unseen or diverse data.
 
-[More Information Needed]
 
-### Recommendations
+## How to Get Started with the Model
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+Use the code below to get started with the model.
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+from transformers import pipeline
 
-## How to Get Started with the Model
+# Initialize the translation pipeline
+pipe = pipeline("translation", model="alpha2002/eng_alpha_darija", tokenizer="alpha2002/eng_alpha_darija")
 
-Use the code below to get started with the model.
+# Translate English to Darija
+input_text = "Hello, how are you?"
+translation = pipe(input_text, src_lang="en_XX", tgt_lang="ar_AR")
 
-[More Information Needed]
+print("Translation:", translation[0]['translation_text'])
 
 ## 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]
+The model was trained on a custom dataset containing parallel English and Darija sentences. 
+The dataset was preprocessed to include language tokens specific to mBART's requirements.
 
 ### 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]
-
+The English text was tokenized with the <en_XX> token, and the Darija text with the <ar_AR> token.
 
 #### 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 -->
+- **Training regime:**  FP16 mixed precision was used during training to improve performance.
+  Training was done on Google Colab using a subset of the data, with gradient accumulation to handle larger batch sizes.
 
-#### Speeds, Sizes, Times [optional]
 
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+#### Speeds, Sizes, Times [optional]
 
-[More Information Needed]
+The model was trained for 2 epochs with a batch size of 4, using the Seq2SeqTrainer from the Hugging Face Transformers library.
 
 ## 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
+The model was evaluated on a small set of held-out test sentences: 100 samples.
 
-<!-- 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]
+BLEU score was used to measure translation accuracy.
 
 ### Results
 
-[More Information Needed]
+The model achieved a BLEU score of 11.6 on the test set, 
+indicating a reasonable level of accuracy given the complexity of translating between languages with different scripts and linguistic structures.
 
-#### 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 Type:** Google Colab GPU (NVIDIA Tesla K80)
+- **Hours used:** Approximately 2 hours for training and 1hour for testing.
 
-#### 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]
+@misc{lahnouki2024eng_alpha_darija,
+  author = {Aicha Lahnouki},
+  title = {English-to-Darija Translation Model},
+  year = {2024},
+  url = {https://huggingface.co/alpha2002/eng_alpha_darija},
+}
 
 ## Model Card Authors [optional]
 
-[More Information Needed]
-
+Lahnouki Aicha
 ## Model Card Contact
 
-[More Information Needed]
+email: aichalahnouki@gmail.com