Skip to content
Snippets Groups Projects
Commit a0e1d311 authored by paul.best's avatar paul.best
Browse files

add early stop pand tiny fix

parent 52770838
Branches
No related tags found
No related merge requests found
......@@ -79,7 +79,7 @@ frontend = {
STFT(nfft, int((sampleDur*sr - nfft)/128)),
MelFilter(sr, nfft, n_mel, 0, sr//2),
Log1p(7, trainable=False),
nn.Instancenorm2d(1),
nn.InstanceNorm2d(1),
u.Croper2D(n_mel, 128)
),
'logSTFT': lambda sr, nfft, sampleDur, n_mel : nn.Sequential(
......
......@@ -47,7 +47,7 @@ loader = torch.utils.data.DataLoader(u.Dataset(df, f'{args.specie}/audio/', meta
batch_size=args.batch_size, shuffle=True, num_workers=8, prefetch_factor=8, collate_fn=u.collate_fn)
MSE = torch.nn.MSELoss()
step = 0
step, NMIs = 0, []
for epoch in range(100_000//len(loader)):
for x, name in tqdm(loader, desc=str(epoch), leave=False):
optimizer.zero_grad()
......@@ -100,7 +100,8 @@ for epoch in range(100_000//len(loader)):
df.loc[idxs, 'cluster'] = clusters.astype(int)
mask = ~df.loc[idxs].label.isna()
clusters, labels = clusters[mask], df.loc[idxs[mask]].label
writer.add_scalar('NMI HDBSCAN', metrics.normalized_mutual_info_score(labels, clusters), step)
NMIs.append(metrics.normalized_mutual_info_score(labels, clusters))
writer.add_scalar('NMI HDBSCAN', NMIs[-1], step)
try:
writer.add_scalar('ARI HDBSCAN', metrics.adjusted_rand_score(labels, clusters), step)
except:
......@@ -151,6 +152,11 @@ for epoch in range(100_000//len(loader)):
writer.add_histogram('K-Means Precisions ', np.array(precs), step)
writer.add_histogram('K-Means Recalls ', np.array(recs), step)
df.drop('cluster', axis=1, inplace=True)
if len(NMIs) > 10 and max(NMIs) > max(NMIs[-10:]):
print('\rEarly stop')
exit()
print('\r', end='')
model[1:].train()
step += 1
0% Loading or .
You are about to add 0 people to the discussion. Proceed with caution.
Please register or to comment