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When i fit an model, save the model, load it again and retrain the model, it seems that this doesn't work ...
model = TS2Vec(input_dims=5, batch_size = 64, device="cuda", max_train_length=680, output_dims=32, lr=0.001) loss_log = model.fit(dvt_data, n_epochs=3, verbose=True) model.save(f"model.sd")
Epoch #0: loss=2.07257523319938 Epoch #1: loss=1.1711310916765094 Epoch #2: loss=0.9953813534158445
for ts2iter in range(5): model = TS2Vec(input_dims=5, batch_size = 64, device="cuda", max_train_length=680, output_dims=32, lr=0.001) model = TS2Vec.load("model.sd") loss_log = model.fit(dvt_data, n_epochs=1, verbose=True) model.save(f"model.sd")
Epoch #0: loss=2.0144058981869803 Epoch #0: loss=2.1384957409088194 Epoch #0: loss=1.9966144137437456 Epoch #0: loss=2.0894507004875837 Epoch #0: loss=2.028488379587132
The text was updated successfully, but these errors were encountered:
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When i fit an model, save the model, load it again and retrain the model, it seems that this doesn't work ...
model = TS2Vec(input_dims=5, batch_size = 64, device="cuda", max_train_length=680, output_dims=32, lr=0.001)
loss_log = model.fit(dvt_data, n_epochs=3, verbose=True)
model.save(f"model.sd")
Epoch #0: loss=2.07257523319938
Epoch #1: loss=1.1711310916765094
Epoch #2: loss=0.9953813534158445
for ts2iter in range(5):
model = TS2Vec(input_dims=5, batch_size = 64, device="cuda", max_train_length=680, output_dims=32, lr=0.001)
model = TS2Vec.load("model.sd")
loss_log = model.fit(dvt_data, n_epochs=1, verbose=True)
model.save(f"model.sd")
Epoch #0: loss=2.0144058981869803
Epoch #0: loss=2.1384957409088194
Epoch #0: loss=1.9966144137437456
Epoch #0: loss=2.0894507004875837
Epoch #0: loss=2.028488379587132
The text was updated successfully, but these errors were encountered: