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"""Utilities for visualizing the training process and results."""
import matplotlib.pyplot as plt
import torch
def plot(path):
"""Plots the losses over the epochs"""
train_losses = []
test_losses = []
cers = []
wers = []
epoch = 5
while True:
try:
current_state = torch.load(path + str(epoch), map_location=torch.device("cpu"))
except FileNotFoundError:
break
train_losses.append((epoch, current_state["train_loss"].item()))
test_losses.append((epoch, current_state["test_loss"]))
cers.append((epoch, current_state["avg_cer"]))
wers.append((epoch, current_state["avg_wer"]))
epoch += 5
plt.plot(*zip(*train_losses), label="train_loss")
plt.plot(*zip(*test_losses), label="test_loss")
plt.plot(*zip(*cers), label="cer")
plt.plot(*zip(*wers), label="wer")
plt.xlabel("epoch")
plt.ylabel("score")
plt.title("Model performance for 5n epochs")
plt.legend()
plt.savefig("losses.svg")
if __name__ == "__main__":
plot("data/runs/epoch")
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