validation-scripts

# ML Training Validation Scripts

**Purpose:** Production-ready validation and testing utilities for ML training workflows. Ensures data quality, model integrity, pipeline correctness, and dependency availability before and during training.

**Activation Triggers:**
- Validating training datasets before fine-tuning
- Checking model checkpoints and outputs
- Testing end-to-end training pipelines
- Verifying system dependencies and GPU availability
- Debugging training failures or data issues
- Ensuring data format compliance
- Validating model configurations
- Testing inference pipelines

**Key Resources:**
- `scripts/validate-data.sh` - Comprehensive dataset validation
- `scripts/validate-model.sh` - Model checkpoint and config validation
- `scripts/test-pipeline.sh` - End-to-end pipeline testing
- `scripts/check-dependencies.sh` - System and package dependency checking
- `templates/test-config.yaml` - Pipeline test configuration template
- `templates/validation-schema.json` - Data validation schema template
- `examples/data-validation-example.md` - Dataset validation workflow
- `examples/pipeline-testing-example.md` - Complete pipeline testing guide

## Quick Start

### Validate Training Data
```bash
bash scripts/validate-data.sh \
  --data-path ./data/train.jsonl \
  --format jsonl \
  --schema templates/validation-schema.json
```

### Validate Model Checkpoint
```bash
bash scripts/validate-model.sh \
  --model-path ./checkpoints/epoch-3 \
  --framework pytorch \
  --check-weights
```

### Test Complete Pipeline
```bash
bash scripts/test-pipeline.sh \
  --config templates/test-config.yaml \
  --data ./data/sample.jsonl \
  --verbose
```

### Check System Dependencies
```bash
bash scripts/check-dependencies.sh \
  --framework pytorch \
  --gpu-required \
  --min-vram 16
```

## Validation Scripts

### 1. Data Validation (validate-data.sh)

**Purpose:** Validate training datasets for format compliance, data quality, and schema conformance.

**Usage:**
```bash
bash s