<commit_before>#!/bin/sh

PARLAI=/path/to/ParlAI                 # Where ParlAI exists in filesystem

DATE=`date +"%Y%m%d"`
SWEEP_NAME=memnn_bAbI_parameter_sweep  # Sweep name
JOBSCRIPTS=scripts
mkdir -p ${JOBSCRIPTS}

SAVE_ROOT=/checkpoint/kshuster/${DATE}/${SWEEP_NAME}
mkdir -p stdout stderr

# Training parameters
ltim=10                                # log every 10 seconds
vtim=900                               # run validation every 900 seconds
vme=10000                              # max examples for validation
vp=-1                                  # validation patience; -1 means infinite patience
vmt=f1                                 # validation metric
ttim=252000                            # max training time (=70 hours)
bs=128                                 # batch size
dmf=20                                 # min frequency of words to keep in dictionary
dmexs=10000000                         # max number of examples to build dict on


# Job Creation Loop(s)
for lr in 0.1 0.01 0.001; do           # learning rate
for esz in 32 64 128; do               # embedding size
for hops in 2 3; do                    # memory hops
for memsize in 100; do                 # memory size
for tfs in 1; do                       # whether to use time features
for penc in 0 1; do                    # whether to use positional encoding
for dr in 0.1; do                      # dropout
for optm in adam; do                   # optimizer<commit_msg>Generalize save root<commit_after>#!/bin/sh

PARLAI=/path/to/ParlAI                 # Where ParlAI exists in filesystem

DATE=`date +"%Y%m%d"`
SWEEP_NAME=memnn_bAbI_parameter_sweep  # Sweep name
JOBSCRIPTS=scripts
mkdir -p ${JOBSCRIPTS}

SAVE_ROOT=/path/to/model/save/root     # Where to save the model files
                                       # (e.g. /tmp/${DATE}/${SWEEP_NAME})
mkdir -p stdout stderr

# Training parameters
ltim=10                                # log every 10 seconds
vtim=900                               # run validation every 900 seconds
vme=10000                              # max examples for validation
vp=-1                                  # validation patience; -1 means infinite patience
vmt=f1                                 # validation metric
ttim=252000                            # max training time (=70 hours)
bs=128                                 # batch size
dmf=20                                 # min frequency of words to keep in dictionary
dmexs=10000000                         # max number of examples to build dict on


# Job Creation Loop(s)
for lr in 0.1 0.01 0.001; do           # learning rate
for esz in 32 64 128; do               # embedding size
for hops in 2 3; do                    # memory hops
for memsize in 100; do                 # memory size
for tfs in 1; do                       # whether to use time features
for penc in 0 1; do                    # whether to use positional encoding
for dr in 0.1; do                      # dropout
for optm in adam; do                   # optimizer
{'fraction_non_alphanumeric': 0.06158940397350993, 'fraction_numerical': 0.04304635761589404, 'mean_word_length': 1.341860465116279, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 2, 'word_list_counts': {'cursed_substrings.json': 18, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '2542225', 'n_tokens_mistral': 911, 'n_tokens_neox': 763, 'n_words': 299}