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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
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- name: reward
dtype: float64
- name: generation_ms
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- name: scoring_ms
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- name: total_ms
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- 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] | |