Update README.md

README.md

@@ -29,116 +29,20 @@ tags:
 
 Just like my teacher gave me homework, i thought maybe we can also add some of these basics on the trainings of our models.
 
-It was created with this code, if you add more complex operations and so.. please share the code :D thank you
-```py
-import random
-# Define the number of samples you want to generate
-num_samples = 500000
-# Define the range for the random numbers
-min_value = -99.99
-max_value = 99.99
-# Define the arithmetic operations
-operations = ['+', '-', '*', '/']
-# Generate data
-data = []
-for _ in range(num_samples):
-    num1 = float("%.3f" % random.uniform(min_value, max_value))
-    num2 = float("%.3f" % random.uniform(min_value, max_value))
-    while num2 == 0.0:
-         num2 = float("%.3f" % random.uniform(min_value, max_value))
-    while num1 == 0.0:
-         num1 = float("%.3f" % random.uniform(min_value, max_value))
-    operation = random.choice(operations)
-    if operation == '/':
-        result = num1 / num2
-    elif operation == '-':
-        result = num1 - num2
-    elif operation == '*':
-        result = num1 * num2
-    elif operation == '+':
-        result = num1 + num2
-    output = "%.4f" % result
-    instruction = f"{num1} {operation} {num2}"
-    data.append({'instruction': instruction, 'output': output})
-# Create the dataset
-import json
-out_file = 'arithmetic-float4a.json'
-with open(out_file, 'w') as f:
-    json.dump(data, f)
-```
+It was created with very simple code that is in the repo, if you add more complex operations and so.. please share the code :D thank you
 
-We have also a new community submission for a more complex dataset of 3 elements:
-```py
-import random
-import json
-import operator
+Note to contributors:
+**thank you to those contributing on the experiment with beautiful commits and good spirit**
+* The model needs some splits
+* The complexity has to be gradual as show in experiments
+* Feel free to contribute on the readme Evaluation tests.
+* Lets aim to build an ablation & paper together. All contributors will be cited.
+* Add your log entry on the version so we can keep a track, thanks.
 
-# Define the number of samples you want to generate
-num_samples = 500000
-# Define the range for the random numbers
-min_value = -99.99
-max_value = 99.99
-# Define the arithmetic operations and their corresponding functions
-operations = {
-    '+': operator.add,
-    '-': operator.sub,
-    '*': operator.mul,
-    '/': operator.truediv
-}
+* 
+## Versions
+24.01.24 Added gradual complexity on a separate script
+20-23.01.24 Multiple contributions with operations and increased complexity on the main generator script.
 
-def generate_random_number():
-    return float("%.3f" % random.uniform(min_value, max_value))
-
-def safe_division(numerator, denominator):
-    return numerator if denominator == 0 else numerator / denominator
-
-# Generate complex data
-data = []
-for _ in range(num_samples):
-    num1 = generate_random_number()
-    num2 = generate_random_number()
-    num3 = generate_random_number()
-    # Ensure num2 and num3 are not zero if they will be used as divisors
-    if num2 == 0.0:
-        num2 = generate_random_number()
-    if num3 == 0.0:
-        num3 = generate_random_number()
-
-    # Randomly choose two operations
-    operation1 = random.choice(list(operations.keys()))
-    operation2 = random.choice(list(operations.keys()))
-    
-    # Create a more complex expression
-    if random.choice([True, False]):
-        # With parentheses
-        expression = f"({num1} {operation1} {num2}) {operation2} {num3}"
-        if operation1 == '/':
-            intermediate_result = safe_division(num1, num2)
-        else:
-            intermediate_result = operations[operation1](num1, num2)
-        if operation2 == '/' and intermediate_result != 0:
-            result = safe_division(intermediate_result, num3)
-        else:
-            result = operations[operation2](intermediate_result, num3)
-    else:
-        # Without parentheses
-        expression = f"{num1} {operation1} {num2} {operation2} {num3}"
-        if operation1 == '/':
-            intermediate_result = safe_division(num1, num2)
-        else:
-            intermediate_result = operations[operation1](num1, num2)
-        if operation2 == '/':
-            result = safe_division(intermediate_result, num3)
-        else:
-            result = operations[operation2](intermediate_result, num3)
-
-    output = "%.4f" % result
-    data.append({'instruction': expression, 'output': output})
-
-# Create the dataset
-out_file = 'arithmetic-float-complex.json'
-with open(out_file, 'w') as f:
-    json.dump(data, f)
-```
 If you use Simple Math o train your model, please cite on the modelcard or the paper.
 Thank you