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code-mt5-base

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code-mt5-base / log_eval.py

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	# To add a new cell, type '# %%'
	# To add a new markdown cell, type '# %% [markdown]'
	# %%
	# from IPython import get_ipython

	# %%
	# get_ipython().system("ls -l ../logs")


	# %%
	# get_ipython().system(" cat ../logs/model_big.log")


	# %%
	path = "code-mt5.log"
	losses = []
	steps = []
	eval_steps = []
	eval_losses = []
	eval_accs = []
	learning_rate = []
	with open(path, "r") as filePtr:
	for line in filePtr:
	# print(line)
	toks = line.split()
	if toks[0] == "Step...":
	if "Learning" in toks:
	losses.append(float(toks[4].split(",")[0]))
	steps.append(int(toks[1].split("(")[1]))
	learning_rate.append(float(toks[-1].split(")")[0]))
	if "Acc:" in toks:
	eval_steps.append(int(toks[1].split("(")[1]))
	eval_losses.append(float(toks[4].split(",")[0]))
	eval_accs.append(float(toks[-1].split(")")[0]))


	# %%
	import matplotlib.pyplot as plt

	# %%
	# print(losses)
	# print(steps)


	# %%
	print("Steps done: ", len(losses) * 100)


	# %%
	print("last 30 losses: ", losses[-30:])


	# %%
	plt.plot(steps, losses)
	plt.show()


	# %%
	min_loss, at_step = 1e10, None
	for step, loss in zip(steps, losses):
	if loss < min_loss:
	min_loss = loss
	at_step = step

	print("min loss: {} at step {}".format(min_loss, at_step))


	# %%
	print(eval_losses)


	# %%
	plt.plot(eval_steps, eval_losses)
	plt.show()


	# %%
	print(eval_accs)


	# %%
	plt.plot(eval_steps, eval_accs)
	plt.show()


	# %%
	plt.plot(steps, learning_rate)
	plt.show()


	# %%