How to configure early stopping? #9
Description
The readme says to point to the train/best directory for decoding a trained model, but the code doesn't seem to be saving any models to that directory. It is saving models to the train directory, which I can successfully evaluate. How can I configure training to save the best model during training?
Here is the command I am running to train:
python main.py train \
--data_path data2/ \
--model_dir train \
--model_name deepatt \
--vocab_path data/word_dict data/label_dict \
--emb_path data/glove.6B.100d.txt \
--model_params=feature_size=100,hidden_size=200,filter_size=800,residual_dropout=0.2,num_hidden_layers=10,attention_dropout=0.1,relu_dropout=0.1 \
--training_params=batch_size=4096,eval_batch_size=1024,optimizer=Adadelta,initializer=orthogonal,use_global_initializer=false,initializer_gain=1.0,train_steps=600000,learning_rate_decay=piecewise_constant,learning_rate_values=[1.0,0.5,0.25],learning_rate_boundaries=[400000,500000],device_list=[0],clip_grad_norm=1.0 \
--validation_params=script=run.sh