File size: 2,526 Bytes
f9073ae |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 |
import re
import matplotlib.pyplot as plt
log_file = '/home/hui007/rna/first_stage/log/train_20250811_2359_totalbatchsize256/train_20250811_2359.log' # 替换为你的log文件名
steps = []
contrast_losses = []
denoising_losses = []
avg_losses = []
with open(log_file, 'r') as f:
for line in f:
match = re.search(
r'Step: (\d+), avg_contrast_loss: ([-\d.]+), avg_denoising_loss: ([-\d.]+), Avg Loss: ([-\d.]+)',
line
)
if match:
step = int(match.group(1))
contrast_loss = float(match.group(2))
denoising_loss = float(match.group(3))
avg_loss = float(match.group(4))
steps.append(step)
contrast_losses.append(contrast_loss)
denoising_losses.append(denoising_loss)
avg_losses.append(avg_loss)
# 画图
plt.figure(figsize=(8, 5))
plt.plot(steps, contrast_losses, label='Avg Contrast Loss')
plt.plot(steps, denoising_losses, label='Avg Denoising Loss')
plt.plot(steps, avg_losses, label='Avg Loss')
plt.xlabel('Step')
plt.ylabel('Loss')
plt.title('Loss over Training Steps')
plt.grid(True)
plt.legend()
plt.tight_layout()
# 保存为 PNG 文件
plt.savefig('/home/hui007/rna/first_stage/figures/loss_vs_step_v3.png', dpi=300)
plt.close()
# log_file = '/home/hui007/rna/first_stage/second_stage.log' # 替换为你的log文件名
# steps = []
# avg_nce_losses = []
# avg_mlm_losses = []
# avg_losses = []
# with open(log_file, 'r') as f:
# for line in f:
# match = re.search(
# r'Step: (\d+), avg_nce_loss: ([-\d.]+), avg_mlm_loss: ([-\d.]+), Avg Loss: ([-\d.]+)',
# line
# )
# if match:
# step = int(match.group(1))
# avg_nce_loss = float(match.group(2))
# avg_mlm_loss = float(match.group(3))
# avg_loss = float(match.group(4))
# steps.append(step)
# avg_nce_losses.append(avg_nce_loss)
# avg_mlm_losses.append(avg_mlm_loss)
# avg_losses.append(avg_loss)
# # 画图
# plt.figure(figsize=(8, 5))
# plt.plot(steps, avg_nce_losses, label='Avg Contrast Loss')
# plt.plot(steps, avg_mlm_losses, label='Avg MLM Loss')
# plt.plot(steps, avg_losses, label='Avg Loss')
# plt.xlabel('Step')
# plt.ylabel('Loss')
# plt.title('Loss over Training Steps')
# plt.grid(True)
# plt.legend()
# plt.tight_layout()
# # 保存为 PNG 文件
# plt.savefig('/home/hui007/rna/first_stage/figures/loss_vs_step_2nd.png', dpi=300)
# plt.close()
|