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metrics.jsonl

@@ -294,3 +294,77 @@
 {"timestamp": 1787809897.6967657, "elapsed_hours": 0.33448189728789857, "event": "step", "step": 5180, "loss": 4.33948887348175, "lr": 2.4242444263399285e-05}
 {"timestamp": 1787809901.447933, "elapsed_hours": 0.33552388807137806, "event": "step", "step": 5200, "loss": 4.389039692878723, "lr": 2.4199306512022486e-05}
 {"timestamp": 1787809905.2048664, "elapsed_hours": 0.336567480829027, "event": "step", "step": 5220, "loss": 4.376558241844177, "lr": 2.4156051933958392e-05}
+{"timestamp": 1787809910.0362163, "elapsed_hours": 0.3379095223877165, "event": "step", "step": 5240, "loss": 4.4124456310272215, "lr": 2.4112681185537416e-05}
+{"timestamp": 1787809914.687498, "elapsed_hours": 0.3392015451192856, "event": "sample", "step": 5250, "prompt": "Write a Python function that returns the nth Fibonacci number.", "sample": "def get_nth_fibonacci(n):\n    fibonacci = 0\n\n    for i in range(1, n + 1):\n        if (n % i) == 0:\n            fibonacci = fibonacci + fibonacci ** 2\n\n    return fibonacci\n\n# test the function with higher values of n\nprint(get_nth_fibonacci(\"15\")) # Output: 15<|im_end|>", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
+{"timestamp": 1787809923.3767953, "elapsed_hours": 0.3416152387195163, "event": "step", "step": 5260, "loss": 4.402317781448364, "lr": 2.4069194924852697e-05}
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+{"timestamp": 1787809946.8244126, "elapsed_hours": 0.3481284659438663, "event": "step", "step": 5380, "loss": 4.372386784553528, "lr": 2.3805888676004238e-05}
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+{"timestamp": 1787809953.4997394, "elapsed_hours": 0.34998272326257496, "event": "sample", "step": 5400, "prompt": "What is the time complexity of binary search and why?", "sample": "As an AI language model, I don't have personal preferences for binary search. However, I can provide a general example in Python while ensuring that it is already quick and efficient:\n\n```python\ndef binary_search(arr, min=0):  # Initialize maximum number of elements to be traversed\n  max = arr[min] - 1\n\n for i in range(1, min:ft+1): # Check if the current element is greater\n  mid = (sum((i - 1) % i for j in arr[i]) // 2)\n\n return max, mid\n```<|im_end|>", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
+{"timestamp": 1787809957.4000218, "elapsed_hours": 0.3510661350356208, "event": "step", "step": 5420, "loss": 4.3654645776748655, "lr": 2.3717225942825996e-05}
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+{"timestamp": 1787809976.9499512, "elapsed_hours": 0.35649667104085286, "event": "step", "step": 5520, "loss": 4.3898863697052, "lr": 2.3493664498384723e-05}
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+{"timestamp": 1787809987.0324638, "elapsed_hours": 0.359297368923823, "event": "sample", "step": 5550, "prompt": "Write a Python function to check if a string is a palindrome.", "sample": "def is_palindrome(s):\n    \"\"\"Check if a string is a palindrome.\"\"\"\n\n    # Iterate over each character in the given string.\n    for char in s:\n        if is_palindrome(char):\n            return True\n\n    # Check for palindromes that are not in the string.\n    for char in s:\n        if is_palindrome(char):\n            return False\n\n    # Check for non-alphanumeric characters.\n    if is_palindrome(s):\n        return True\n\n    # Return True if string is a palindrome, else False.\n    return False<|im", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
+{"timestamp": 1787809989.2864292, "elapsed_hours": 0.35992347048388584, "event": "step", "step": 5560, "loss": 4.286239976882935, "lr": 2.3403492323400586e-05}
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+{"timestamp": 1787810009.1198506, "elapsed_hours": 0.36543275422520105, "event": "step", "step": 5660, "loss": 4.336290078163147, "lr": 2.317624078023742e-05}
+{"timestamp": 1787810012.708928, "elapsed_hours": 0.36642972018983627, "event": "step", "step": 5680, "loss": 4.381134810447693, "lr": 2.3130483796108505e-05}
+{"timestamp": 1787810016.6284912, "elapsed_hours": 0.3675184878375795, "event": "step", "step": 5700, "loss": 4.432169499397278, "lr": 2.3084626203248676e-05}
+{"timestamp": 1787810019.4496062, "elapsed_hours": 0.36830213069915774, "event": "sample", "step": 5700, "prompt": "Explain the difference between a stack and a queue.", "sample": "Buffer and queue are two distinct elements in a stack. If we take the top element of an array, each position would have different values for other elements too; and if you use that value to identify how many items are on the stack.\nWhen I say \"stack\" and \"queue\", the elements in a question should have different values for other elements. The first element is an array, like this:\n```python\n[1, 2, 3, 4]\n```  #change to stack and queue (which will be the same)\n[2, 4, 5, 6, 7]\n```<|im_end|>", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787810034.926334, "elapsed_hours": 0.3726012217336231, "event": "step", "step": 5780, "loss": 4.391124911308289, "lr": 2.2900203683731137e-05}
+{"timestamp": 1787810038.749088, "elapsed_hours": 0.37366309795114727, "event": "step", "step": 5800, "loss": 4.387562880516052, "lr": 2.2853853514794106e-05}
+{"timestamp": 1787810042.5142744, "elapsed_hours": 0.3747089829709795, "event": "step", "step": 5820, "loss": 4.365669703483581, "lr": 2.2807406934620997e-05}
+{"timestamp": 1787810046.242928, "elapsed_hours": 0.3757447202338113, "event": "step", "step": 5840, "loss": 4.341605143547058, "lr": 2.276086464797659e-05}
+{"timestamp": 1787810049.8121736, "elapsed_hours": 0.3767361772060394, "event": "sample", "step": 5850, "prompt": "Write a Python function to find the maximum element in a list.", "sample": "Here is a Python function that does what you described:\n```python\ndef find_max(lst):  # Assuming list contains only integers\n    max_element = [i for i in lst if i not in ['a', 'b']] # Print the maximum element\n    return max_element<|im_end|>", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787810081.0050845, "elapsed_hours": 0.385400874680943, "event": "sample", "step": 6000, "prompt": "Write a Python function that returns the nth Fibonacci number.", "sample": "Here is a Python function that calculates the nth Fibonacci number:\n```python\ndef fib(n): \n  return len(fib) + 1 if n <= 0 else fib[-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": 1787810111.896561, "elapsed_hours": 0.39398184034559464, "event": "step", "step": 6120, "loss": 4.4007504320144655, "lr": 2.2099621513449883e-05}
+{"timestamp": 1787810115.7911143, "elapsed_hours": 0.39506366067462495, "event": "step", "step": 6140, "loss": 4.414657287597656, "lr": 2.2051729163381255e-05}
+{"timestamp": 1787810119.5722463, "elapsed_hours": 0.39611397518051994, "event": "sample", "step": 6150, "prompt": "What is the time complexity of binary search and why?", "sample": "The time complexity of binary search is O(n) because the query size could factor significantly, so it's not possible to perform this in a linear-time manner. This means that binary search is always faster and can be more efficient than large data structures like unsorted lists, sorting keys in reverse order, or even having a time complexity of O(n log n) where n is the number of elements.<|im_end|>", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
+{"timestamp": 1787810121.639159, "elapsed_hours": 0.39668811758359274, "event": "step", "step": 6160, "loss": 4.37192020893097, "lr": 2.200375257324166e-05}
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+{"timestamp": 1787810148.5992239, "elapsed_hours": 0.4041770244306988, "event": "step", "step": 6300, "loss": 4.356054821014404, "lr": 2.166561902892071e-05}
+{"timestamp": 1787810157.4181442, "elapsed_hours": 0.4066267246007919, "event": "sample", "step": 6300, "prompt": "Write a Python function to check if a string is a palindrome.", "sample": "Here's a Python function that checks if a string is palindrome:\n```python\ndef is_palindromic(string): \n    # Check for palindrome with a length of 2^10  \n    char_count = len(string) - 1\n\n    # Loop through all characters in the string and check if they are palindromes\n    for i in range(len(string)): \n\n        # Check if the character is a palindrome\n        for j in range(i, len(string)): \n\n            # Check if the character is a palindrome\n            if char_count % 2 == 0: \n\n    # Check f", "has_open": false, "has_close": false, "has_end": false, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787810180.84249, "elapsed_hours": 0.41313348723782434, "event": "step", "step": 6420, "loss": 4.336105871200561, "lr": 2.137272398254391e-05}
+{"timestamp": 1787810184.5561244, "elapsed_hours": 0.4141650524404314, "event": "step", "step": 6440, "loss": 4.388781757354736, "lr": 2.1323645030786426e-05}
+{"timestamp": 1787810189.792694, "elapsed_hours": 0.41561965511904825, "event": "sample", "step": 6450, "prompt": "Explain the difference between a stack and a queue.", "sample": "A stack and a queue are two different things. A stack is an element in the same order, while a queue is an operation that adds or removes elements from another stack and will return an output for the given purpose. Some properties of Stack are:\n- The number of stack elements (i.e., their order) is equal to that of a stack (i.e., it must be an integer).\n- The number of queue elements (i, j, k) is equal to the sum of all the elements in a queue.\n   - Shuffle out an element from both stacks (i and ", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787810203.7091544, "elapsed_hours": 0.4194853384627236, "event": "step", "step": 6520, "loss": 4.369629492759705, "lr": 2.11266047637502e-05}