log_eval.py

# 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()


# %%