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metrics.jsonl

@@ -741,3 +741,75 @@
 {"timestamp": 1787811701.4485724, "elapsed_hours": 0.8355240658256743, "event": "step", "step": 13060, "loss": 4.413706812858582, "lr": 5.726953851082467e-06}
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 {"timestamp": 1787811709.0516603, "elapsed_hours": 0.8376360345549053, "event": "step", "step": 13100, "loss": 4.384546623229981, "lr": 5.663897878259244e-06}
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+{"timestamp": 1787811725.4074376, "elapsed_hours": 0.8421793060832553, "event": "step", "step": 13180, "loss": 4.359521040916443, "lr": 5.539762792781546e-06}
+{"timestamp": 1787811729.1339798, "elapsed_hours": 0.8432144567701552, "event": "step", "step": 13200, "loss": 4.399514427185059, "lr": 5.509143617829136e-06}
+{"timestamp": 1787811730.4567192, "elapsed_hours": 0.8435818843046824, "event": "sample", "step": 13200, "prompt": "Explain the difference between a stack and a queue.", "sample": "In an array, a stack is commonly called a queue (or \"queue\") because it's the same as a single node or tree. This means that if you're doing this, then your stack is somewhere in between nodes (or blocks) which are both not the same node or tree.<|im_end|>", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787811758.27718, "elapsed_hours": 0.8513097902139027, "event": "step", "step": 13340, "loss": 4.356433334350586, "lr": 5.299504694939267e-06}
+{"timestamp": 1787811766.4367347, "elapsed_hours": 0.853576333059205, "event": "sample", "step": 13350, "prompt": "Write a Python function to find the maximum element in a list.", "sample": "Here is a Python function that finds the maximum element in an array.\n\n```python \ndef max_element(arr):\n    if len(arr) <= 1:\n        return \"The length of the list is greater than or equal to 1.\"\n\n    max_element = 0\n    for i in range(1, len(arr)):\n        if arr[i] > max_element:\n            max_element = i\n\n    return max(max_element)\n```\nHere's a code snippet to simulate this function:\n\n```python\ndef find_maximum_elements(lst):  # for each element in the list \n\n    max_element = 0\n    for i", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787811797.7583926, "elapsed_hours": 0.8622767935858833, "event": "sample", "step": 13500, "prompt": "Write a Python function that returns the nth Fibonacci number.", "sample": "Here is a Python function that returns the nth Fibonacci number:\n```python\ndef f(n):  # Generate Fibonacci numbers from 1 to n in range from 0 to 100 \n    if (n < 1 or n > 100):  # Calculate Fibonacci numbers\n    return fib(f(\"1\", \"0\")) + fib(n)\n\n\n# Test the function with an example  **Output:** 4<|im_end|>", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787811840.8888793, "elapsed_hours": 0.8742574843433168, "event": "sample", "step": 13650, "prompt": "What is the time complexity of binary search and why?", "sample": "The time complexity of binary search is O(n), where n is the number of elements in an array. In this case, we are asking for a function that would return an object from another list or by converting it to integer and returning the current number.\n\nHere is how you could do this: \n```python\ndef binary_search(arr, n):\n    if len(arr) == 0 or not arr[0]: return \"Error: Array is empty\"\n\n    min_length = 1\n    for i in range(1, len(arr)):\n        if arr[i] > min_length: return \"Error: Array is empty\"\n", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787811846.684213, "elapsed_hours": 0.8758672993712955, "event": "step", "step": 13680, "loss": 4.364566011428833, "lr": 4.825345194203434e-06}
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+{"timestamp": 1787811862.3541834, "elapsed_hours": 0.8802200688918431, "event": "step", "step": 13760, "loss": 4.357516164779663, "lr": 4.721143313152249e-06}
+{"timestamp": 1787811866.205967, "elapsed_hours": 0.8812900086906221, "event": "step", "step": 13780, "loss": 4.423383922576904, "lr": 4.695538682462054e-06}
+{"timestamp": 1787811870.0788321, "elapsed_hours": 0.8823658045795228, "event": "step", "step": 13800, "loss": 4.417260475158692, "lr": 4.670113168697386e-06}
+{"timestamp": 1787811878.807594, "elapsed_hours": 0.8847904607322481, "event": "sample", "step": 13800, "prompt": "Write a Python function to check if a string is a palindrome.", "sample": "Here is a Python function to check if a string, palindrome and empty_arr are palindromes:\n```python\ndef isPalindrome(string):\n  return str(str(random.choice(\"abc\", \"abc\"))[::-1]) in string\n\ndef palindrome_concatenate(string):\n  reversed = \"\"\n  for i in range(len(string) - 1, 0, -1):\n    if string[i] == \"\" or not str.isalpha():\n      reversed += string + 'a' if i % 2 != 0 else string[i:]\n  return reverse(reversed)\n\ndef isPalindrome_reverse(string):\n  reversed = \"\"\n  for i in range(len(string)-1, ", "has_open": false, "has_close": false, "has_end": false, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787811890.684202, "elapsed_hours": 0.8880895186132854, "event": "step", "step": 13860, "loss": 4.384010887145996, "lr": 4.594915173314117e-06}
+{"timestamp": 1787811894.6134465, "elapsed_hours": 0.8891809752914641, "event": "step", "step": 13880, "loss": 4.37028293132782, "lr": 4.5702099579673424e-06}
+{"timestamp": 1787811898.3202503, "elapsed_hours": 0.8902106430795458, "event": "step", "step": 13900, "loss": 4.363791608810425, "lr": 4.545685761242008e-06}
+{"timestamp": 1787811902.3684459, "elapsed_hours": 0.8913351418574651, "event": "step", "step": 13920, "loss": 4.383414454460144, "lr": 4.521342955260025e-06}
+{"timestamp": 1787811906.2470057, "elapsed_hours": 0.8924125195211834, "event": "step", "step": 13940, "loss": 4.410268607139588, "lr": 4.497181909390945e-06}
+{"timestamp": 1787811910.8950398, "elapsed_hours": 0.8937036400371128, "event": "sample", "step": 13950, "prompt": "Explain the difference between a stack and a queue.", "sample": "A stack and a queue are two different types of elements. They all have the same size, meaning that they do not need to be allocated individually in order for them to work together properly and with each other. A queue is a collection of elements, where the original items are shared among all items in an array that have been allocated to it. The inner stack also has public keys and a private key, which can refer to the unique elements available for one item in an array (for example `i`).\nEach ele", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787811920.4027557, "elapsed_hours": 0.8963446723090278, "event": "step", "step": 14000, "loss": 4.373474321365356, "lr": 4.425792984753778e-06}
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+{"timestamp": 1787811932.4256294, "elapsed_hours": 0.8996843595637215, "event": "step", "step": 14060, "loss": 4.371828103065491, "lr": 4.356052933040994e-06}
+{"timestamp": 1787811936.498985, "elapsed_hours": 0.9008158471186956, "event": "step", "step": 14080, "loss": 4.358286285400391, "lr": 4.333174317944788e-06}
+{"timestamp": 1787811940.3445613, "elapsed_hours": 0.9018840626213286, "event": "step", "step": 14100, "loss": 4.415607743263244, "lr": 4.310480318169096e-06}
+{"timestamp": 1787811946.229043, "elapsed_hours": 0.9035186408625708, "event": "sample", "step": 14100, "prompt": "Write a Python function to find the maximum element in a list.", "sample": " Here's a Python function to find the maximum element in an array with elements from a list. This is very simple and may require more steps depending on your specific problem and requirements or use of the function's built-in functions to search for items in an array.\n\n```python\ndef find_max(arr):\n    max = arr[0]\n\n    for i in range(1, len(arr) + 1):\n        if arr[i] < max:\n            max = arr[i]\n\n    return max\n```\nThis function iterates over the list, checking if each element is found in a", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
+{"timestamp": 1787811950.3697927, "elapsed_hours": 0.9046688493092855, "event": "step", "step": 14120, "loss": 4.423531579971313, "lr": 4.2879712780650365e-06}
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+{"timestamp": 1787811965.6226933, "elapsed_hours": 0.9089057660102844, "event": "step", "step": 14200, "loss": 4.406164608001709, "lr": 4.1997915030509145e-06}
+{"timestamp": 1787811969.5462654, "elapsed_hours": 0.909995647072792, "event": "step", "step": 14220, "loss": 4.404484701156616, "lr": 4.178212328163259e-06}
+{"timestamp": 1787811973.409038, "elapsed_hours": 0.9110686395565669, "event": "step", "step": 14240, "loss": 4.378333168029785, "lr": 4.156820119937227e-06}
+{"timestamp": 1787811977.560994, "elapsed_hours": 0.9122219606902864, "event": "sample", "step": 14250, "prompt": "Write a Python function that returns the nth Fibonacci number.", "sample": "Here is a Python function that returns the nth Fibonacci number:\n```python\ndef fib(n): \n    if not isinstance(n, int) or n <= 1: return 0\n    sum = 0\n    while len(sum) < n and (x >= 2**n) * x <= n: return f\"{sum} is a fibonacci number!\"\n    Fibonacci(x, n-1)<|im_end|>", "has_open": false, "has_close": false, "has_end": true, "reasoning_len": 0, "is_real_reasoning": false}
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+{"timestamp": 1787812001.4684017, "elapsed_hours": 0.9188629072242313, "event": "step", "step": 14340, "loss": 4.359061822891236, "lr": 4.052674840098911e-06}
+{"timestamp": 1787812005.59906, "elapsed_hours": 0.92001031226582, "event": "step", "step": 14360, "loss": 4.365929260253906, "lr": 4.032411148767955e-06}
+{"timestamp": 1787812009.3807197, "elapsed_hours": 0.921060773399141, "event": "step", "step": 14380, "loss": 4.359287276268005, "lr": 4.012336636436678e-06}