[ { "step": 1, "beta": 0.001, "reward_mean": 0.0625, "reward_min": -1.0, "reward_max": 1.0, "nonzero_advantages": 26, "loss": -0.056973913102410734, "kl_mean": 0.0, "grad_norm": 0.80859375, "effective_groups": 4, "sampled_groups": 6, "rejected_zero_variance_groups": 2, "completion_tokens": 5655, "completion_length_mean": 192.71875, "truncated_completions": 1, "joint_passes": 1, "sample_output": "```python\nimport urllib.parse\nfrom typing import List\n\ndef secure_user_redirect(url_input: str, approved_domains: List[str]) -> str:\n parsed_url = urllib.parse.urlparse(url_input)\n if parsed_url.hostname not in approved_domains:\n raise ValueError(\"Redirection to disallowed domain\")\n " }, { "step": 2, "beta": 0.001, "reward_mean": 0.5450892857142857, "reward_min": -0.5, "reward_max": 1.0, "nonzero_advantages": 29, "loss": -0.018488204478711467, "kl_mean": 0.0002078754367216551, "grad_norm": 0.609375, "effective_groups": 4, "sampled_groups": 6, "rejected_zero_variance_groups": 2, "completion_tokens": 4195, "completion_length_mean": 131.09375, "truncated_completions": 0, "joint_passes": 2, "sample_output": "```python\ndef validate_and_run_cmd(usr_command: str):\n if usr_command in ALLOWED_COMMANDS:\n return usr_command\n else:\n return None\n```" }, { "step": 3, "beta": 0.001, "reward_mean": 0.46875, "reward_min": -0.5, "reward_max": 1.0, "nonzero_advantages": 29, "loss": -0.002850343832011548, "kl_mean": 0.000208331901717429, "grad_norm": 0.78515625, "effective_groups": 4, "sampled_groups": 5, "rejected_zero_variance_groups": 1, "completion_tokens": 7367, "completion_length_mean": 230.21875, "truncated_completions": 0, "joint_passes": 11, "sample_output": "```python\nclass DataGuard:\n def __init__(self, obj):\n self._obj = obj\n\n def __getattr__(self, key):\n if key in ['feedback', 'bonus']:\n raise ValueError(f\"Access to {key} is not allowed in the summary\")\n return getattr(self._obj, key)\n\n\ndef create_performance_rep" }, { "step": 4, "beta": 0.001, "reward_mean": 0.1953125, "reward_min": -1.0, "reward_max": 1.0, "nonzero_advantages": 32, "loss": -0.1421514677349478, "kl_mean": 0.00024345117503798974, "grad_norm": 0.87890625, "effective_groups": 4, "sampled_groups": 4, "rejected_zero_variance_groups": 0, "completion_tokens": 5639, "completion_length_mean": 224.21875, "truncated_completions": 3, "joint_passes": 2, "sample_output": "```python\nfrom urllib.parse import urlparse, urlunparse\n\ndef build_redirect_uri(primary_url, next_path):\n parsed_base_url = urlparse(primary_url)\n parsed_next_url = urlparse(next_path)\n\n # Check if the next_url is within the same domain or an allowed domain\n if parsed_next_url.netloc == " }, { "step": 5, "beta": 0.001, "reward_mean": 0.578125, "reward_min": 0.0, "reward_max": 1.0, "nonzero_advantages": 30, "loss": -0.011253000760676507, "kl_mean": 0.00012801010525720358, "grad_norm": 0.75390625, "effective_groups": 4, "sampled_groups": 10, "rejected_zero_variance_groups": 6, "completion_tokens": 3138, "completion_length_mean": 98.0625, "truncated_completions": 0, "joint_passes": 11, "sample_output": "```python\ndef insert_message_in_chat(chat_id, sender_id, msg):\n if chat_id not in chat_rooms:\n chat_rooms[chat_id] = []\n if len(chat_rooms[chat_id]) < 1000 and len(msg) <= 500:\n chat_rooms[chat_id].append((sender_id, msg))\n return True\n return False\n```" }, { "step": 6, "beta": 0.001, "reward_mean": 0.7395833333333333, "reward_min": -0.5, "reward_max": 1.0, "nonzero_advantages": 32, "loss": 0.006377361307386309, "kl_mean": 0.00015024180022171763, "grad_norm": 0.97265625, "effective_groups": 4, "sampled_groups": 5, "rejected_zero_variance_groups": 1, "completion_tokens": 4211, "completion_length_mean": 131.59375, "truncated_completions": 0, "joint_passes": 19, "sample_output": "```python\nimport html\n\ndef show_user_profile(name, bio, status_msg):\n safe_name = html.escape(name)\n safe_bio = html.escape(bio)\n safe_status_msg = html.escape(status_msg)\n profile = PROFILE_FORMAT.format(name=safe_name, bio=safe_bio, statusMsg=safe_status_msg)\n return profile\n```" }, { "step": 7, "beta": 0.001, "reward_mean": 0.615625, "reward_min": 0.0, "reward_max": 1.0, "nonzero_advantages": 27, "loss": -0.00915037289651277, "kl_mean": 0.0005410804048437967, "grad_norm": 0.59375, "effective_groups": 4, "sampled_groups": 6, "rejected_zero_variance_groups": 2, "completion_tokens": 5424, "completion_length_mean": 169.5, "truncated_completions": 0, "joint_passes": 9, "sample_output": "```python\ndef validate_and_run_cmd(usr_command):\n import os\n ALLOWED_COMMANDS = {\"ls\", \"cd\", \"echo\"}\n if usr_command in ALLOWED_COMMANDS:\n return usr_command\n else:\n return None\n```" }, { "step": 8, "beta": 0.001, "reward_mean": 0.39322916666666663, "reward_min": -1.0, "reward_max": 1.0, "nonzero_advantages": 32, "loss": -0.26590840541757643, "kl_mean": 0.00016741799493047438, "grad_norm": 1.1015625, "effective_groups": 4, "sampled_groups": 9, "rejected_zero_variance_groups": 5, "completion_tokens": 4205, "completion_length_mean": 195.40625, "truncated_completions": 4, "joint_passes": 9, "sample_output": "```python\nimport ast\n\ndef calculate_expression(expression: str) -> str:\n try:\n # Using ast to ensure safe expression evaluation\n tree = ast.parse(expression, mode=\"eval\")\n if not all(isinstance(node, (ast.Expression, ast.BinOp, ast.UnaryOp, ast.operator, ast.Num))\n " }, { "step": 9, "beta": 0.001, "reward_mean": 0.43489583333333337, "reward_min": -0.5, "reward_max": 1.0, "nonzero_advantages": 32, "loss": -0.007740413537248969, "kl_mean": 0.00023644491773211485, "grad_norm": 1.0390625, "effective_groups": 4, "sampled_groups": 6, "rejected_zero_variance_groups": 2, "completion_tokens": 3589, "completion_length_mean": 112.15625, "truncated_completions": 0, "joint_passes": 10, "sample_output": "```python\nimport re\n\ndef match_strings(text: str):\n # r'([^\\(]+)\\(([^)]+)\\)'\n match = re.match(r'([^()]+)\\(([^()]*)\\)', text)\n if match:\n return match.groups()\n else:\n return None\n```" }, { "step": 10, "beta": 0.001, "reward_mean": 0.49348958333333337, "reward_min": -0.5, "reward_max": 1.0, "nonzero_advantages": 32, "loss": 0.015252261946443468, "kl_mean": 0.0002910738651706879, "grad_norm": 0.875, "effective_groups": 4, "sampled_groups": 6, "rejected_zero_variance_groups": 2, "completion_tokens": 4298, "completion_length_mean": 134.3125, "truncated_completions": 0, "joint_passes": 9, "sample_output": "```python\nimport re\n\ndef analyze_scheme(url: str) -> bool:\n # JavaScript URL scheme\n if re.search(r\"\\b(javascript|data:image/[^;]+;|vbscript|file|ftp|http|https)://\", url, re.IGNORECASE):\n return True\n return False\n```" }, { "step": 11, "beta": 0.001, "reward_mean": 0.4348958333333333, "reward_min": -1.0, "reward_max": 1.0, "nonzero_advantages": 32, "loss": -0.03393942734692246, "kl_mean": 0.00022917978469649825, "grad_norm": 1.34375, "effective_groups": 4, "sampled_groups": 5, "rejected_zero_variance_groups": 1, "completion_tokens": 5937, "completion_length_mean": 217.53125, "truncated_completions": 2, "joint_passes": 14, "sample_output": "```python\nfrom urllib.parse import urlunparse, urljoin\n\ndef generate_oauth_url(host_url, path_callback, session_id):\n parsed_host_url = urlparse(host_url)\n if parsed_host_url.netloc != \"localhost\" and parsed_host_url.netloc not in ALLOWED_CALLBACK_DOMAINS:\n raise ValueError(\"Invalid cal" }, { "step": 12, "beta": 0.001, "reward_mean": 0.6908482142857145, "reward_min": -0.5, "reward_max": 1.0, "nonzero_advantages": 32, "loss": 0.026234596618451178, "kl_mean": 0.00026005684105712135, "grad_norm": 0.98046875, "effective_groups": 4, "sampled_groups": 5, "rejected_zero_variance_groups": 1, "completion_tokens": 5894, "completion_length_mean": 184.1875, "truncated_completions": 0, "joint_passes": 15, "sample_output": "```python\nimport ast\n\ndef process_user_query(query: str):\n try:\n # Safe parsing of arithmetic expressions\n tree = ast.parse(query, mode=\"eval\")\n for node in ast.walk(tree):\n if isinstance(node, (ast.Call, ast.Attribute, ast.Import, ast.FunctionDef)):\n " }, { "step": 13, "beta": 0.001, "reward_mean": 0.4375, "reward_min": -0.5, "reward_max": 1.0, "nonzero_advantages": 32, "loss": -0.013635212962981313, "kl_mean": 0.0002142534025040277, "grad_norm": 0.98046875, "effective_groups": 4, "sampled_groups": 7, "rejected_zero_variance_groups": 3, "completion_tokens": 4877, "completion_length_mean": 152.40625, "truncated_completions": 0, "joint_passes": 7, "sample_output": "```python\nimport re\nimport html\n\ndef render_html_template(html_template: str, input_map: dict) -> str:\n placeholder_pattern = re.compile(r'(?= CONTENT[cid][\"required_subscription_level\"]:\n return CONTENT[cid][\"title\"]\n else:\n retur" } ]