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ef0820827a
These experiments were completed a few weeks ago, but I didn't make the PR, pending model release.
Token vector width: 128->96
Hidden width: 128->64
Embed size: 5000->2000
Dropout: 0.2->0.1
Updated optimizer defaults (unclear how important?)
This should improve speed, model size and load time, while keeping
similar or slightly better accuracy.
The tl;dr is we prefer to prevent over-fitting by reducing model size,
rather than using more dropout.
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| .. | ||
| __init__.pxd | ||
| __init__.py | ||
| _beam_utils.pxd | ||
| _beam_utils.pyx | ||
| _parser_model.pxd | ||
| _parser_model.pyx | ||
| _state.pxd | ||
| _state.pyx | ||
| arc_eager.pxd | ||
| arc_eager.pyx | ||
| ner.pxd | ||
| ner.pyx | ||
| nn_parser.pxd | ||
| nn_parser.pyx | ||
| nonproj.pxd | ||
| nonproj.pyx | ||
| stateclass.pxd | ||
| stateclass.pyx | ||
| transition_system.pxd | ||
| transition_system.pyx | ||