Shaer-AI/ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500-splits

--- language: - ar license: apache-2.0 pretty_name: Ashaar Enhanced Description SFT Stratified Splits task_categories: - text-generation size_categories: - 100K<n<1M --- # Ashaar Enhanced Description SFT Stratified Splits Source dataset: - `Shaer-AI/ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500` Target dataset: - `Shaer-AI/ashaar-with-enhanced-descriptions-baseform-final-sft-lte20-min500-splits` This dataset publishes deterministic `train / eval / test` splits with a `94 / 3 / 3` policy. ## Split policy Primary stratification key: - `base_meter` - `form` - `length_bucket` Length buckets: - `1-3` - `4-6` - `7-10` - `11-20` Small groups fall back gracefully to coarser stratification levels when needed. ## Counts - train: **109070** - eval: **3481** - test: **3481** ## Stratification fallback levels used - `base_meter_form_length_bucket`: **116032** - `base_meter_form`: **0** - `base_meter`: **0** - `global`: **0** ## Notes - `sampler_group` keeps the fine-grained joint group `base_meter||form||length_bucket` - `split_group` is the actual group used to allocate split quotas after fallback - weighted sampling should be applied only on the `train` split