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This repository has been archived by the owner on Dec 21, 2023. It is now read-only.
In [5]: model = tc.activity_classifier.create(data, 'exp_id', 'activity', varbose=False)
Pre-processing 639438 samples...
Using sequences of size 2000 for model creation.
Processed a total of 52 sessions.
Using GPU to create model (AMD Radeon Pro 560X)
+--------------+----------------+--------------+---------------------+-----------------+--------------+
| Iteration | Train Accuracy | Train Loss | Validation Accuracy | Validation Loss | Elapsed Time |
+--------------+----------------+--------------+---------------------+-----------------+--------------+
| 1 | 0.56555 | 1.08477 | 0.701665 | 1.34365 | 12.53s |
| 2 | 0.806943 | 0.546507 | 0.737116 | 0.896359 | 14.19s |
| 3 | 0.865909 | 0.374496 | 0.789828 | 0.615451 | 15.83s |
| 4 | 0.889123 | 0.29769 | 0.806484 | 0.542623 | 17.47s |
| 5 | 0.900577 | 0.255274 | 0.804695 | 0.548907 | 19.17s |
| 6 | 0.908086 | 0.225594 | 0.809228 | 0.606536 | 21.01s |
| 10 | 0.928016 | 0.159004 | 0.819507 | 0.565104 | 28.42s |
+--------------+----------------+--------------+---------------------+-----------------+--------------+
In all the toolkits (mentioned above), passing verbose=False should not print progress table. This flag is not yet working in C++ implementations for all the toolkits.
The text was updated successfully, but these errors were encountered:
In all the toolkits (mentioned above), passing verbose=False should not print progress table. This flag is not yet working in C++ implementations for all the toolkits.
The text was updated successfully, but these errors were encountered: