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metrics.jsonl

@@ -368,3 +368,76 @@
 {"timestamp": 1787810195.5992312, "elapsed_hours": 0.417232582171758, "event": "step", "step": 6480, "loss": 4.4084877681732175, "lr": 2.1225268295987838e-05}
 {"timestamp": 1787810199.5177538, "elapsed_hours": 0.4183210606707467, "event": "step", "step": 6500, "loss": 4.381596584320068, "lr": 2.1175972005682234e-05}
 {"timestamp": 1787810203.7091544, "elapsed_hours": 0.4194853384627236, "event": "step", "step": 6520, "loss": 4.369629492759705, "lr": 2.11266047637502e-05}
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+{"timestamp": 1787810220.3869407, "elapsed_hours": 0.42411805702580346, "event": "step", "step": 6600, "loss": 4.374450879096985, "lr": 2.0928441277306478e-05}
+{"timestamp": 1787810222.2365265, "elapsed_hours": 0.4246318309836917, "event": "sample", "step": 6600, "prompt": "Write a Python function to find the maximum element in a list.", "sample": "def find_max(lst):\n    max_element = set()\n\n    for element in lst:\n      if isinstance(element, list):\n        max_element.add((element * (max_element)))\n\n   return max(min(max), key=lambda x: 0, reverse=True)<|im_end|>", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787810241.6953447, "elapsed_hours": 0.430037058128251, "event": "step", "step": 6700, "loss": 4.33701418876648, "lr": 2.0679230707950204e-05}
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+{"timestamp": 1787810253.3981485, "elapsed_hours": 0.4332878369092941, "event": "sample", "step": 6750, "prompt": "Write a Python function that returns the nth Fibonacci number.", "sample": "Here is the Python function that returns the nth Fibonacci number:\n```python\ndef fib(n): \n  if len(list(range(1, n+2))) == 1 and n+2 < 7: \n   return f\"{n} is a Fibonacci number of {list(range(-1, 1))}\" \n```<|im_end|>", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787810298.0266068, "elapsed_hours": 0.44568463093704647, "event": "sample", "step": 6900, "prompt": "What is the time complexity of binary search and why?", "sample": "The time complexity of binary search is O(n^2) where n is the length of the input.\nIn this case, we are using two nested loops to perform binary search on a left and right row (and thenaggregate). As the goal is to find the largest elements in an iterated array, we can use a simple binary search algorithm.\nHere's how:\n1. Initialize two pointers n and i to -1 (inclusive) \n2. Get the current index of element in left row (and then null value; if the left node is equal to its right child, it means t", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787810325.5575154, "elapsed_hours": 0.4533321055438783, "event": "step", "step": 7040, "loss": 4.389763555526733, "lr": 1.9820627131117636e-05}
+{"timestamp": 1787810336.5758896, "elapsed_hours": 0.45639276497893866, "event": "sample", "step": 7050, "prompt": "Write a Python function to check if a string is a palindrome.", "sample": "Here is a Python function that checks if a string is a palindrome:\n\n```python\ndef check_palindrome(String):   # Remove non-alphanumeric characters from the string\n\n    # Iterate through all strings in a group of characters\n    for i, char in enumerate(String):\n        # Check if the current character is a palindrome\n        char_index = i - 1\n\n        # Check if the current index is greater than (char_index + 1)\n        while char_index < i:\n            # Check if the current character is a pali", "has_open": false, "has_close": false, "has_end": false, "reasoning_len": 0, "is_real_reasoning": false}
+{"timestamp": 1787810338.3921492, "elapsed_hours": 0.4568972815407647, "event": "step", "step": 7060, "loss": 4.344579429626465, "lr": 1.976963060336991e-05}
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+{"timestamp": 1787810358.0435822, "elapsed_hours": 0.46235601292716133, "event": "step", "step": 7160, "loss": 4.272045798301697, "lr": 1.951391928269033e-05}
+{"timestamp": 1787810362.179817, "elapsed_hours": 0.4635049670272403, "event": "step", "step": 7180, "loss": 4.411787490844727, "lr": 1.9462636714291315e-05}
+{"timestamp": 1787810366.017238, "elapsed_hours": 0.4645709173546897, "event": "step", "step": 7200, "loss": 4.4147289276123045, "lr": 1.9411309191839294e-05}
+{"timestamp": 1787810369.021053, "elapsed_hours": 0.46540531045860717, "event": "sample", "step": 7200, "prompt": "Explain the difference between a stack and a queue.", "sample": "Elementary functions are a type of data structure that have subkeys, and in some cases they need to be connected. Instead of using the Stack object (OF) it is not necessary for each function to work, but rather a storage in one flow structure that allows you to access items from another flow. \n\nAnd the concept of stack is used for storing and managing this data structure, which means when a node has multiple operations in one flow, it can go through all its nodes on the stack. In both cases it i", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
+{"timestamp": 1787810372.9424095, "elapsed_hours": 0.4664945760700438, "event": "step", "step": 7220, "loss": 4.382910280227661, "lr": 1.9359937494160836e-05}
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+{"timestamp": 1787810388.5892565, "elapsed_hours": 0.4708409224616157, "event": "step", "step": 7300, "loss": 4.437346830368042, "lr": 1.915402455092586e-05}
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+{"timestamp": 1787810396.3178108, "elapsed_hours": 0.47298774308628505, "event": "step", "step": 7340, "loss": 4.355011839866638, "lr": 1.9050823325588928e-05}
+{"timestamp": 1787810401.7947538, "elapsed_hours": 0.4745091161462996, "event": "sample", "step": 7350, "prompt": "Write a Python function to find the maximum element in a list.", "sample": "def find_max(lst):\n  max_element = None\n\n  def get_largest(lst, pivot: int) -> str:\n  return lower_bound.node(val=pivot, upper_bound=[])\n\n  def max_element(lst):\n    # Step 1: Find the maximum element in a list.\n    max_iter = len(minor)\n\n    for i, curr in enumerate(lst):\n      if curr < max_iter:\n        minor = curr\n\n    return \"\".join(max_element) + \"\\n\"\n\n\n# Example usage:\nprint()<|im_end|>", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
+{"timestamp": 1787810403.6337364, "elapsed_hours": 0.47501994457509783, "event": "step", "step": 7360, "loss": 4.428941969871521, "lr": 1.899916426328275e-05}
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+{"timestamp": 1787810419.5622685, "elapsed_hours": 0.47944453683164384, "event": "step", "step": 7440, "loss": 4.329614787101746, "lr": 1.8792156646410896e-05}
+{"timestamp": 1787810423.5983005, "elapsed_hours": 0.4805656568871604, "event": "step", "step": 7460, "loss": 4.387472033500671, "lr": 1.8740315826617036e-05}
+{"timestamp": 1787810427.6408043, "elapsed_hours": 0.48168857468499077, "event": "step", "step": 7480, "loss": 4.41569151878357, "lr": 1.8688441013024366e-05}
+{"timestamp": 1787810431.3493145, "elapsed_hours": 0.48271871632999847, "event": "step", "step": 7500, "loss": 4.414827327728272, "lr": 1.863653299276386e-05}
+{"timestamp": 1787810434.0557706, "elapsed_hours": 0.48347050964832305, "event": "sample", "step": 7500, "prompt": "Write a Python function that returns the nth Fibonacci number.", "sample": "Here is the Python function that returns the nth Fibonacci number:\n```python\ndef f(n): \n    if n < 0: \n      return None, None\n\n    fib_sum = [0] * (n - 1) + [f(i)]\n    for _ in range(2, n+1):\n\n        fib_sum.append(f(n - 1))\n    return fib_sum[::-1]\n```<|im_end|>", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787810467.3125103, "elapsed_hours": 0.49270849287509916, "event": "step", "step": 7640, "loss": 4.349042782783508, "lr": 1.8272313286041393e-05}
+{"timestamp": 1787810472.495937, "elapsed_hours": 0.49414833386739093, "event": "sample", "step": 7650, "prompt": "What is the time complexity of binary search and why?", "sample": "An example of binary search in Python is as follows:\n\n```python\ndef binary_search(n, mid=0):  # start with an empty sorted list\n  n = [1] * (mid + 1)  # there are two elements where the middle item is greater than or equal to mid - 1\n  while n < len(n):  # I've checked all strings from left to right  -- so I can't reverse the list\n    n += [2] * mid + 1  # there's only one element in this sorted list.\n\n  return (n, end)\n```<|im_end|>", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
+{"timestamp": 1787810474.3651094, "elapsed_hours": 0.4946675482061174, "event": "step", "step": 7660, "loss": 4.377892932891846, "lr": 1.822016800710563e-05}
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+{"timestamp": 1787810497.8390346, "elapsed_hours": 0.5011880829599169, "event": "step", "step": 7780, "loss": 4.39210391998291, "lr": 1.7906775927498368e-05}
+{"timestamp": 1787810501.8639317, "elapsed_hours": 0.5023061099317339, "event": "step", "step": 7800, "loss": 4.340878047943115, "lr": 1.785446457707847e-05}
+{"timestamp": 1787810507.5084774, "elapsed_hours": 0.5038740393850538, "event": "sample", "step": 7800, "prompt": "Write a Python function to check if a string is a palindrome.", "sample": "Here is a Python function that checks if a string can be palindrome:\n\n```python\ndef check_palindromes(string):\n    # Check if the string is a palindrome and return True\n    pass\n\n    def sort(s):\n        # Sort the string in reverse order (in case of a palindrome)\n        sorted_string = sorted(s, ''.join((',')))\n\n    # Check if the string can contain any palindrome\n    for i in range(len(s)):  \n\n    # If all characters are alphanumeric, return True\n    if sorted_string[my_string] == 'aeiou':\n\n ", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}