WER plots for finetuning on the AWB dataset

import matplotlib.pyplot as plt
import pandas as pd

MINS_DATA = """
5	0.057692307692307696
10	0.057692307692307696
15	0.05576923076923077
20	0.046153846153846156
25	0.038461538461538464
30	0.046153846153846156
35	0.03653846153846154
40	0.03653846153846154
45	0.025
50	0.03653846153846154
55	0.026923076923076925
60	0.032692307692307694
"""

mins = []
wer = []
for line in MINS_DATA.split("\n"):
    if "\t" in line:
        parts = line.split("\t")
        mins.append(int(parts[0]))
        wer.append(float(parts[1]) * 100)

pd.options.display.float_format = '{:,.2f}'.format
df = pd.DataFrame(data={"Minutes": mins, "WER": wer})

df

	Minutes	WER
0	5	5.77
1	10	5.77
2	15	5.58
3	20	4.62
4	25	3.85
5	30	4.62
6	35	3.65
7	40	3.65
8	45	2.50
9	50	3.65
10	55	2.69
11	60	3.27

import numpy as np
ax = plt.gca()
ax.set_xticks(np.arange(5, 125, 5))
ax.set_xticklabels(labels=mins, minor=True)

df.plot(kind='line', x='Minutes', y='WER', ax=ax)

<matplotlib.axes._subplots.AxesSubplot at 0x7f271c39dcd0>