selimc/OrpoGemma-2-9B-TR
TEXT GENERATIONConcurrency Cost:1Model Size:9BQuant:FP8Ctx Length:16kPublished:Nov 20, 2024License:gemmaArchitecture:Transformer0.0K Warm
OrpoGemma-2-9B-TR is a 9 billion parameter Gemma-2 model, fine-tuned by selimc specifically for the Turkish language. It leverages the ORPO training technique on a 1500-row Turkish dataset to enhance its fluency and contextual understanding in Turkish. This model excels at generating coherent and detailed responses in Turkish, making it suitable for various Turkish natural language processing tasks.
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OrpoGemma-2-9B-TR: Turkish Fine-tuned Gemma-2 Model
OrpoGemma-2-9B-TR is a 9 billion parameter language model developed by selimc, representing a Turkish fine-tuned version of Google's Gemma-2-9B-IT. This model was specifically optimized for Turkish language generation and understanding using the ORPO (Odds Ratio Preference Optimization) training technique.
Key Capabilities
- Turkish Language Fluency: Produces coherent, contextually appropriate, and fluent text in Turkish.
- Detailed Response Generation: Capable of delivering informative and comprehensive answers across a wide array of instructions and question types.
- ORPO Fine-tuning: Utilizes the ORPO Trainer on a subset of 1500 rows from the
selimc/orpo-dpo-mix-TR-20kdataset, enhancing its performance in Turkish. - Performance Metrics: Achieves an average score of 55.9% on the OpenLLMTurkishLeaderboard_v0.2 across various Turkish benchmarks, including MMLU_TR_V0.2 (53.0%) and GSM8K_TR_V0.2 (64.8%).
Good For
- Applications requiring high-quality text generation in Turkish.
- Developing chatbots or conversational AI systems for Turkish-speaking users.
- Tasks that benefit from detailed and contextually relevant responses in Turkish.