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6.55 kB
| dataset_info: | |
| features: | |
| - name: instruction | |
| dtype: string | |
| - name: input | |
| dtype: float64 | |
| - name: output | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 743535 | |
| num_examples: 800 | |
| - name: validation | |
| num_bytes: 87504 | |
| num_examples: 100 | |
| - name: test | |
| num_bytes: 92879 | |
| num_examples: 100 | |
| download_size: 360936 | |
| dataset_size: 923918 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| - split: validation | |
| path: data/validation-* | |
| - split: test | |
| path: data/test-* | |
| # Dataset Analysis Report | |
| ## Dataset Format | |
| The dataset is provided in **Parquet** format with the following structure: | |
| | Field | Description | | |
| | ------------- | ----------------------------------------------- | | |
| | `instruction` | Instruction or question provided to the model | | |
| | `input` | Additional input or contextual information | | |
| | `output` | Expected response generated for the instruction | | |
| ## Dataset Statistics | |
| | Metric | Result | | |
| | --------------------------- | -----: | | |
| | Total rows | 1,000 | | |
| | Valid rows | 1,000 | | |
| | Invalid rows | 0 | | |
| | Columns | 3 | | |
| | Expected fields per row | 3 | | |
| | Rows with missing fields | 0 | | |
| | Rows with unexpected fields | 0 | | |
| ### Fields | |
| ```text | |
| ['input', 'instruction', 'output'] | |
| ``` | |
| ## Duplicate Analysis | |
| | Check | Result | | |
| | -------------------------------- | -----: | | |
| | Exact duplicate rows | 0 | | |
| | Duplicate groups | 0 | | |
| | Duplicate instructions | 215 | | |
| | Duplicate responses | 2 | | |
| | Near-duplicate instruction pairs | 69 | | |
| No exact duplicate rows were detected. However, **215 duplicate instructions**, **2 duplicate responses**, and **69 near-duplicate instruction pairs** were identified. | |
| ## Quality Analysis | |
| The automated analysis identified the following quality flags: | |
| | Quality Issue | Rows | Percentage | | |
| | -------------------------------- | ----: | ---------: | | |
| | English words detected | 1,000 | 100.00% | | |
| | Missing values | 1,000 | 100.00% | | |
| | Low Devanagari ratio | 93 | 9.30% | | |
| | HTML noise | 21 | 2.10% | | |
| | URLs detected | 16 | 1.60% | | |
| | Potentially incomplete responses | 10 | 1.00% | | |
| > **Important:** The `missing_values` check flagged all 1,000 rows. This means the automated analysis identified at least one field as missing according to its configured missing-value rules. The result should be manually reviewed, particularly for the `input` field, because an intentionally empty `input` may be a valid characteristic of an instruction/input/output dataset rather than an actual data-quality error. | |
| ## Analysis Summary | |
| ```text | |
| Total rows : 1,000 | |
| Flagged rows : 1,000 | |
| Flagged percentage : 100.00% | |
| Data status : ANALYSIS ONLY | |
| Cleaning performed : NO | |
| ``` | |
| All 1,000 rows were flagged by at least one automated quality check. Being flagged does **not necessarily mean that every row is unusable**; it means that every row requires review according to the configured analysis rules. | |
| ## Overall Dataset Quality | |
| | Metric | Result | | |
| | --------------------- | -------------- | | |
| | Overall Quality Score | 66.40 / 100 | | |
| | Quality Grade | D | | |
| | Dataset Status | NEEDS CLEANING | | |
| ### Strengths | |
| * No exact duplicate rows detected. | |
| * No possible PII detected. | |
| * All rows follow the expected `instruction` / `input` / `output` schema. | |
| * All 1,000 rows are valid records according to the analysis. | |
| ### Identified Issues | |
| * 215 duplicate instructions detected. | |
| * 2 duplicate responses detected. | |
| * English words were detected in all 1,000 rows. | |
| * 21 rows contain HTML noise. | |
| * 16 rows contain URLs. | |
| * 10 responses were potentially incomplete. | |
| * 93 rows have a low Devanagari ratio. | |
| * The automated analysis flagged missing values in all 1,000 rows. | |
| * 69 near-duplicate instruction pairs were identified. | |
| ## Recommendation | |
| Significant cleaning and manual review are recommended before using this dataset for model training. | |
| Priority should be given to reviewing: | |
| 1. Duplicate and near-duplicate instructions. | |
| 2. The 100% missing-value flag, especially whether empty `input` fields are intentional. | |
| 3. English-word detection across the dataset. | |
| 4. Low-Devanagari-ratio records. | |
| 5. HTML noise and URLs. | |
| 6. Potentially incomplete responses. | |
| ## Analysis Method | |
| The dataset was analyzed without modifying the original data. | |
| The analysis included: | |
| * Dataset structure and schema validation | |
| * Missing-value detection | |
| * Exact duplicate detection | |
| * Duplicate instruction detection | |
| * Duplicate response detection | |
| * Near-duplicate instruction detection | |
| * English-word detection | |
| * Devanagari-ratio analysis | |
| * HTML-noise detection | |
| * URL detection | |
| * Potential incomplete-response detection | |
| * Possible PII detection | |
| * Overall dataset quality scoring and grading | |
| ### Cleaning Status | |
| **No cleaning, deletion, modification, or automatic correction was performed during this analysis.** | |
| The analysis script only identified and flagged potential quality issues for subsequent manual review and cleaning. | |
| ## Analysis Outputs | |
| The analysis generated the following files: | |
| ```text | |
| analysis_report(train).json | |
| flagged_rows(train).jsonl | |
| ``` | |
| `analysis_report(train).json` contains the complete dataset-level analysis results, including dataset structure, schema consistency, duplicate statistics, language analysis, quality flags, incomplete-response analysis, and the overall quality score. | |
| `flagged_rows(train).jsonl` contains the individual records flagged by the automated quality checks for manual review. | |
| ## Final Assessment | |
| **Overall Quality Score:** 66.40 / 100 | |
| **Grade:** D | |
| **Status:** NEEDS CLEANING | |
| The dataset has a valid and consistent three-column `instruction` / `input` / `output` structure with 1,000 valid rows and no exact duplicate rows. However, the automated analysis identified duplicate instructions, near-duplicate instructions, duplicate responses, English-word occurrences, missing-value flags, low Devanagari ratios, HTML noise, URLs, and potentially incomplete responses. | |
| The dataset should therefore undergo **manual review and targeted cleaning** before being considered ready for model training. | |