Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+language:
+- en
+- hi
+- el
+metrics:
+- bleu
+base_model:
+- facebook/m2m100_418M
+---
+# Model Card for Multilingual Translation Model
+
+## Model Details
+
+### Model Description
+
+This model is a fine-tuned version of `facebook/m2m100_418M` for multilingual translation tasks. It supports English (`en`), Hindi (`hi`), and Greek (`el`) as source and target languages. The model has been specifically optimized to ensure accurate and fluent translations across these languages.
+
+- **Developed by:** Arun Kumar Roy
+- **Model type:** Transformer-based sequence-to-sequence model for machine translation
+- **Language(s) (NLP):** English, Hindi, Greek
+- **License:** MIT
+- **Finetuned from model:** `facebook/m2m100_418M`
+
+### Model Sources
+
+- **Repository:** [Link to model repository]
+- **Demo [optional]:** [Provide a link if applicable]
+
+## Uses
+
+### Direct Use
+
+This model can be directly used for multilingual machine translation tasks in English, Hindi, and Greek. Use cases include:
+
+- Document translation
+- Real-time conversational translation
+- Educational tools for language learning
+
+### Downstream Use [optional]
+
+The model can be further fine-tuned for domain-specific translation tasks such as medical, legal, or technical documents.
+
+### Out-of-Scope Use
+
+The model may not perform well for:
+- Languages other than English, Hindi, and Greek.
+- Highly informal, dialectical, or domain-specific text without additional fine-tuning.
+- Use cases requiring strict grammatical correctness for complex legal or academic content.
+
+## Bias, Risks, and Limitations
+
+This model inherits potential biases from its training data, which may include:
+- Gender bias in language representation.
+- Cultural or contextual inaccuracies when translating idiomatic expressions.
+
+### Recommendations
+
+Users should:
+- Review translations for critical applications.
+- Be cautious when using the model for sensitive or culturally nuanced content.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model:
+
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("path_to_your_model")
+model = AutoModelForSeq2SeqLM.from_pretrained("path_to_your_model")
+
+inputs = tokenizer("Translate this text", return_tensors="pt")
+outputs = model.generate(**inputs)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Training Details
+
+### Training Data
+
+The model was fine-tuned on a dataset comprising multilingual text pairs for English, Hindi, and Greek. The dataset includes:
+- Publicly available bilingual corpora.
+- Synthetic data for low-resource language pairs.
+
+### Training Procedure
+
+#### Preprocessing
+
+- Tokenization with `facebook/m2m100_418M` tokenizer.
+- Dynamic padding with sequences padded to the longest in the batch.
+
+#### Training Hyperparameters
+
+- **Training regime:** Mixed precision (fp32)
+- **Batch size:** 16
+- **Learning rate:** 2e-5
+- **Number of epochs:** 10
+
+#### Speeds, Sizes, Times [optional]
+
+- Approximate training time: 1218 minutes on M3 Pro chip.
+
+## Evaluation
+
+
+#### Testing Data
+
+The model was evaluated using a held-out test set from the same multilingual dataset used for fine-tuning.
+
+#### Metrics
+
+The primary evaluation metric is BLEU score.
+
+### Results
+
+The model achieved the following BLEU scores:
+- English to Hindi: 36.2
+- English to Greek: 31.5
+
+## Environmental Impact
+
+- **Hardware Type:** M3 Pro Chip (MacBook)
+- **Hours used:** ~1218 Min
+- **Compute Region:** Local
+- **Carbon Emitted:** Negligible (powered by renewable energy sources, where applicable)
+
+## Citation [optional]
+
+**BibTeX:**
+```bibtex
+@misc{arun_translation_model,
+  author = {Arun Kumar Roy},
+  title = {Multilingual Translation Model for English, Hindi, and Greek},
+  year = {2025},
+  publisher = {Hugging Face}
+}
+```
+
+## Model Card Authors
+
+- Arun Kumar Roy
+
+## Model Card Contact
+
+For inquiries, contact [https://github.com/aktheroy].
+