Upload enhanced MarianMT Indonesian-English model with meeting domain adaptation

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README.md

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+---
+language:
+- id
+- en
+license: apache-2.0
+base_model: Helsinki-NLP/opus-mt-id-en
+tags:
+- translation
+- indonesian
+- english
+- marian
+- fine-tuned
+- meeting-translation
+- domain-adaptation
+- enhanced
+pipeline_tag: translation
+datasets:
+- ted_talks_iwslt
+library_name: transformers
+metrics:
+- bleu
+- rouge
+widget:
+- text: "Selamat pagi semuanya, mari kita mulai rapat hari ini."
+  example_title: "Meeting Opening"
+- text: "Tim marketing akan bertanggung jawab untuk strategi ini."
+  example_title: "Task Assignment"
+- text: "Database migration sudah selesai dan berjalan dengan lancar."
+  example_title: "Technical Update"
+---
+
+# Enhanced MarianMT Indonesian-English Translation (Meeting Domain Adaptation)
+
+This model is an **enhanced fine-tuned version** of [Helsinki-NLP/opus-mt-id-en](https://huggingface.co/Helsinki-NLP/opus-mt-id-en) with **domain-specific adaptation** for meeting and business contexts.
+
+## 🎯 Model Highlights
+
+- **Domain Adaptation**: Specialized for meeting and business translation
+- **Enhanced Dataset**: TEDTalks + 2000+ meeting-specific sentence pairs
+- **Improved Performance**: Better BLEU scores on meeting contexts
+- **Robust Training**: 80% dataset usage with domain mixing
+- **Production Ready**: Optimized for real-world meeting scenarios
+
+## 📊 Performance Metrics
+
+| Metric | Base Model | This Model | Improvement |
+|--------|------------|------------|-------------|
+| BLEU Score | 9.146 | **11.747** | **+28.4%** |
+| Translation Speed | 1.2s | **0.12s** | **-90.0%** |
+| Meeting Context | Standard | **Enhanced** | **Domain Adapted** |
+
+## 🚀 Model Details
+
+- **Base Model**: Helsinki-NLP/opus-mt-id-en
+- **Training Dataset**: TEDTalks (80%) + Meeting Domain (10%)
+- **Training Strategy**: Domain adaptation with enhanced learning
+- **Specialization**: Business meetings, technical discussions, formal conversations
+- **Training Date**: 2025-05-28
+- **Languages**: Indonesian (id) → English (en)
+- **License**: Apache 2.0
+
+## 🛠️ Usage
+
+```python
+from transformers import MarianMTModel, MarianTokenizer
+
+# Load model and tokenizer
+model_name = "dhintech/marian-id-en-enhanced"
+tokenizer = MarianTokenizer.from_pretrained(model_name)
+model = MarianMTModel.from_pretrained(model_name)
+
+# Translate Indonesian to English
+def translate(text):
+    inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=128)
+    outputs = model.generate(
+        **inputs,
+        max_length=128,
+        num_beams=3,
+        early_stopping=True,
+        do_sample=False
+    )
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Example usage
+indonesian_text = "Tim marketing akan bertanggung jawab untuk strategi ini."
+english_translation = translate(indonesian_text)
+print(english_translation)
+# Output: "The marketing team will be responsible for this strategy."
+```
+
+## 📝 Example Translations
+
+### Meeting Context Examples
+
+| Indonesian | English | Context |
+|------------|---------|---------|
+| Selamat pagi semuanya, mari kita mulai rapat hari ini. | Good morning everyone, let's start today's meeting. | Meeting Opening |
+| Tim marketing akan bertanggung jawab untuk strategi ini. | The marketing team will be responsible for this strategy. | Task Assignment |
+| Database migration sudah selesai dan berjalan dengan lancar. | Database migration is complete and running smoothly. | Technical Update |
+| Budget yang disetujui adalah 500 juta rupiah. | The approved budget is 500 million rupiah. | Financial Discussion |
+
+## 🎯 Intended Use Cases
+
+- **Business Meeting Translation**: Real-time translation during meetings
+- **Technical Documentation**: Translating technical meeting notes
+- **Corporate Communication**: Formal business correspondence
+- **Project Management**: Translating project updates and reports
+- **Training Materials**: Educational and training content translation
+
+## 📊 Training Configuration
+
+- **Dataset Size**: 69,138 sentence pairs
+- **TEDTalks Data**: 80% of cleaned dataset
+- **Meeting Domain Data**: 10% specialized meeting content
+- **Max Sequence Length**: 128 tokens
+- **Training Epochs**: 12
+- **Learning Rate**: 1e-05
+- **Batch Size**: 12 (effective)
+
+## 🔧 Technical Specifications
+
+- **Model Architecture**: MarianMT (Transformer-based)
+- **Parameters**: ~74M (with selective fine-tuning)
+- **Max Input/Output Length**: 128 tokens
+- **Inference Time**: ~0.12s per sentence
+- **Memory Requirements**:
+  - GPU: 3GB VRAM minimum
+  - CPU: 4GB RAM minimum
+
+## 🚨 Limitations
+
+- **Domain Specificity**: Optimized for formal business/meeting contexts
+- **Informal Language**: May not perform optimally on very casual Indonesian
+- **Regional Dialects**: Trained primarily on standard Indonesian
+- **Cultural Context**: Some cultural nuances may be lost in translation
+
+## 📚 Citation
+
+```bibtex
+@misc{enhanced-marian-id-en-2025,
+  title={Enhanced MarianMT Indonesian-English Translation (Meeting Domain Adaptation)},
+  author={DhinTech},
+  year={2025},
+  publisher={Hugging Face},
+  journal={Hugging Face Model Hub},
+  howpublished={\url{https://huggingface.co/dhintech/marian-id-en-enhanced}},
+  note={Enhanced with TEDTalks and meeting-specific domain adaptation}
+}
+```
+
+## 🙏 Acknowledgments
+
+- **Base Model**: Helsinki-NLP team for the original opus-mt-id-en model
+- **Dataset**: TEDTalks corpus and custom meeting domain data
+- **Framework**: Hugging Face Transformers team
+
+---
+
+*This model is specifically enhanced for Indonesian business meeting translation scenarios with domain adaptation techniques.*

config.json

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+}

generation_config.json

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model_config.json

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+  "model_name": "Enhanced MarianMT Meeting Translation ID-EN",
+  "base_model": "Helsinki-NLP/opus-mt-id-en",
+  "enhancement_date": "2025-05-28T12:42:35.765269",
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+    "total_samples": 69138
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+  ]
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tokenizer_config.json

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