Multi-task Learning with TensorFlow
Tensorflow implementation of multi-task learning. (Language model & Text classification)
Model
Requirements
- Python3
- TensorFlow
- pip install -r requirements.txt
Usage
$ python train.py
Hyperparameters
$ python train.py -h
usage: train.py [-h] [--embedding_size EMBEDDING_SIZE]
[--num_layers NUM_LAYERS] [--num_hidden NUM_HIDDEN]
[--keep_prob KEEP_PROB] [--learning_rate LEARNING_RATE]
[--batch_size BATCH_SIZE] [--num_epochs NUM_EPOCHS]
[--max_document_len MAX_DOCUMENT_LEN]
optional arguments:
-h, --help show this help message and exit
--embedding_size EMBEDDING_SIZE
embedding size.
--num_layers NUM_LAYERS
RNN network depth.
--num_hidden NUM_HIDDEN
RNN network size.
--keep_prob KEEP_PROB
dropout keep prob.
--learning_rate LEARNING_RATE
learning rate.
--batch_size BATCH_SIZE
batch size.
--num_epochs NUM_EPOCHS
number of epochs.
--max_document_len MAX_DOCUMENT_LEN
max document length.
Experimental Results
Language Model Training Loss
Text Classification Training Loss
