@@ -39,7 +39,7 @@ The model was fine-tuned on the **Opus 4.6 dataset** using approximately 1,00,00
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### Detailed Training Steps:
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1. **Dataset Preparation**:
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- - Acquired/gathered the Opus 4.7 dataset containing ~40,000 high-quality samples.
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- Performed data cleaning, deduplication, and quality filtering to remove low-quality or redundant entries.
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- Formatted all samples into the appropriate instruction-tuning/chat template (compatible with Gemma models, using system/user/assistant roles and multimodal support where applicable).
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- Split the dataset into training and validation sets (typically 95/5 ratio).
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### Detailed Training Steps:
40
41
1. **Dataset Preparation**:
42
+ - Acquired/gathered the Opus 4.6 dataset containing ~1.00,000 high-quality samples.
43
- Performed data cleaning, deduplication, and quality filtering to remove low-quality or redundant entries.
44
- Formatted all samples into the appropriate instruction-tuning/chat template (compatible with Gemma models, using system/user/assistant roles and multimodal support where applicable).
45
- Split the dataset into training and validation sets (typically 95/5 ratio).
