---
dataset_info:
  features:
  - name: example_id
    dtype: int64
  - name: prompt
    list:
    - name: content
      dtype: string
    - name: role
      dtype: string
  - name: completion
    list:
    - name: content
      dtype: string
    - name: role
      dtype: string
  - name: task
    dtype: string
  - name: reward
    dtype: float64
  - name: generation_ms
    dtype: float64
  - name: scoring_ms
    dtype: float64
  - name: total_ms
    dtype: float64
  - name: info
    struct:
    - name: pii_count
      dtype: int64
  - name: answer
    dtype: string
  - name: exact_match_reward
    dtype: float64
  - name: pii_count_reward
    dtype: float64
  - name: format_reward_func
    dtype: float64
  splits:
  - name: train
    num_bytes: 176352
    num_examples: 150
  download_size: 26186
  dataset_size: 176352
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
---

# Evaluation Results: Qwen3-4B-Instruct-2507-PII-RL on PII Masking

This dataset contains evaluation results for the RL-trained model [AdamLucek/Qwen3-4B-Instruct-2507-PII-RL](https://huggingface.co/AdamLucek/Qwen3-4B-Instruct-2507-PII-RL) on the [adamlucek/pii-masking](https://app.primeintellect.ai/dashboard/environments/adamlucek/pii-masking) environment from Prime Intellect's Environment Hub. The model was fine-tuned using reinforcement learning to mask personally identifiable information (PII) in text.

## Evaluation Configuration

- **Environment**: [adamlucek/pii-masking](https://app.primeintellect.ai/dashboard/environments/adamlucek/pii-masking)
- **Model**: [AdamLucek/Qwen3-4B-Instruct-2507-PII-RL](https://huggingface.co/AdamLucek/Qwen3-4B-Instruct-2507-PII-RL)
- **Base Model**: [Qwen/Qwen3-4B-Instruct-2507](https://huggingface.co/Qwen/Qwen3-4B-Instruct-2507)
- **Examples Evaluated**: 50
- **Rollouts per Example**: 3
- **Total Samples**: 150

## Performance Summary

### Overall Metrics

| Metric | Mean | Std Dev | Min | Max |
|--------|------|---------|-----|-----|
| **Total Reward** | 0.883 | 0.729 | 0.100 | 1.600 |
| **Exact Match** | 0.500 | 0.502 | 0.000 | 1.000 |
| **PII Count Accuracy** | 0.567 | 0.497 | 0.000 | 1.000 |
| **Format Compliance** | 1.000 | 0.000 | 1.000 | 1.000 |

### Reward Breakdown by Rollout

| Rollout | Mean Reward | Std Dev | Range |
|---------|-------------|---------|-------|
| Rollout 1 | 0.880 | 0.737 | [0.100, 1.600] |
| Rollout 2 | 0.890 | 0.729 | [0.100, 1.600] |
| Rollout 3 | 0.880 | 0.737 | [0.100, 1.600] |