From 92efde015d8dd98f28a2bec5d7bc4a779df40258 Mon Sep 17 00:00:00 2001 From: googol88 Date: Sat, 30 Oct 2021 20:31:52 -0400 Subject: [PATCH 1/3] add supplementary data --- nlp/data/cumulative.csv | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/nlp/data/cumulative.csv b/nlp/data/cumulative.csv index d899897..3fbfde6 100644 --- a/nlp/data/cumulative.csv +++ b/nlp/data/cumulative.csv @@ -1259,4 +1259,16 @@ https://twitter.com/Adobe,taking a break,yes,2020-03-31 17:05:00 +0000 UTC ,procrastinate on my chinese school hw,no ,check the side effects of a medication,yes ,get to know the people im going to school with enxt year,yes -,reach my friends new article,yes \ No newline at end of file +,reach my friends new article,yes +,watch tutorials on knitting,yes +,focusing on my social and emotional wellbeing,yes +,check on my friend’s progress,yes +,trying to fix my broken computer,yes +,getting some inspo for decorating my house,yes +,doing some gift shopping for the holidays,yes +,check when the restaurant opens,yes +,discovering ways to take care of my dog,yes +,learning to tie a tie,yes +,read self-help guides,yes +,managing stress,yes +,taking care of my finances,yes \ No newline at end of file From c9b7ca00a8f34819f3de95d29b5d722dca2adb95 Mon Sep 17 00:00:00 2001 From: googol88 Date: Sun, 31 Oct 2021 13:07:06 -0400 Subject: [PATCH 2/3] add more examples to dataset --- nlp/data/cumulative.csv | 14 +++++++++++++- 1 file changed, 13 insertions(+), 1 deletion(-) diff --git a/nlp/data/cumulative.csv b/nlp/data/cumulative.csv index 3fbfde6..0fdd478 100644 --- a/nlp/data/cumulative.csv +++ b/nlp/data/cumulative.csv @@ -1271,4 +1271,16 @@ https://twitter.com/Adobe,taking a break,yes,2020-03-31 17:05:00 +0000 UTC ,learning to tie a tie,yes ,read self-help guides,yes ,managing stress,yes -,taking care of my finances,yes \ No newline at end of file +,taking care of my finances,yes +,find some fitness videos,yes +,add something to my resume,yes +,looking for some new webtoons,no +,getting away from homework to procastinate later,no +,idk im just bored,no +,getting ready for my next class,yes +,look at some fashion trends,no +,browse cool website designs,no +,looking at tech twitter stuff,no +,get some nfts,no +,buy some crypto,no +,keep track of my stocks,no \ No newline at end of file From e48f7c11f66cbcdc6bd794c4bffb91d2ef77265b Mon Sep 17 00:00:00 2001 From: googol88 Date: Sun, 31 Oct 2021 20:03:14 -0400 Subject: [PATCH 3/3] retrain model with new data --- README.md | 2 +- nlp/data_proc.py | 2 +- nlp/models/acc82.49/details.yml | 7 +++++++ nlp/models/acc82.49/model.json | 1 + nlp/models/acc82.49/tokenizer.json | 1 + nlp/models/acc82.49/weights.h5 | Bin 0 -> 3453088 bytes nlp/net.py | 14 +++++++------- nlp/train.py | 10 +++++----- 8 files changed, 23 insertions(+), 14 deletions(-) create mode 100644 nlp/models/acc82.49/details.yml create mode 100644 nlp/models/acc82.49/model.json create mode 100644 nlp/models/acc82.49/tokenizer.json create mode 100644 nlp/models/acc82.49/weights.h5 diff --git a/README.md b/README.md index 0d2676f..e53f98d 100644 --- a/README.md +++ b/README.md @@ -84,7 +84,7 @@ For local development, you can run the server by doing `python server.py`, which ### Training the NLP Model -You can train a new version of the neural network on the `data/survey.csv` data by doing `python train.py`. This will begin training of a basic 64 cell LSTM model (which is defined in `net.py`). You can configure the training parameters which are constants at the top of `train.py`. +You can train a new version of the neural network on the `data/cumulative.csv` data by doing `python train.py`. This will begin training of a basic 64 cell LSTM model (which is defined in `net.py`). You can configure the training parameters which are constants at the top of `train.py`. ```python TOKENIZER_VOCAB_SIZE = 500 # Vocabulary size of the tokenizer diff --git a/nlp/data_proc.py b/nlp/data_proc.py index de3a032..6ac3510 100644 --- a/nlp/data_proc.py +++ b/nlp/data_proc.py @@ -13,7 +13,7 @@ "havent": "have not", "doesnt": "does not", "he'll": "he will", - "she'll": "she will" + "she'll": "she will" } # remove punctuation from string diff --git a/nlp/models/acc82.49/details.yml b/nlp/models/acc82.49/details.yml new file mode 100644 index 0000000..2250df7 --- /dev/null +++ b/nlp/models/acc82.49/details.yml @@ -0,0 +1,7 @@ +BATCH_SIZE: 128 +NUM_EPOCHS: 20 +SEQUENCE_MAX_LENGTH: 35 +TOKENIZER_VOCAB_SIZE: 1000 +TRAINED_AT: 2021-10-31 18:21:05.743503 +TRAIN_TEST_SPLIT: 0.2 +VALIDATION_SPLIT: 0.2 diff --git a/nlp/models/acc82.49/model.json b/nlp/models/acc82.49/model.json new file mode 100644 index 0000000..8bdabbc --- /dev/null +++ b/nlp/models/acc82.49/model.json @@ -0,0 +1 @@ +{"class_name": "Functional", "config": {"name": "model", "layers": [{"class_name": "InputLayer", "config": {"batch_input_shape": [null, 35], "dtype": "float32", "sparse": false, "ragged": false, "name": "inputs"}, "name": "inputs", "inbound_nodes": []}, {"class_name": "Embedding", "config": {"name": "embedding", "trainable": true, "batch_input_shape": [null, 35], "dtype": "float32", "input_dim": 1000, "output_dim": 128, "embeddings_initializer": {"class_name": "RandomUniform", "config": {"minval": -0.05, "maxval": 0.05, "seed": null}}, "embeddings_regularizer": null, "activity_regularizer": null, "embeddings_constraint": null, "mask_zero": false, "input_length": 35}, "name": "embedding", "inbound_nodes": [[["inputs", 0, 0, {}]]]}, {"class_name": "LSTM", "config": {"name": "lstm", "trainable": true, "dtype": "float32", "return_sequences": true, "return_state": false, "go_backwards": false, "stateful": false, "unroll": false, "time_major": false, "units": 128, "activation": "tanh", "recurrent_activation": "sigmoid", "use_bias": true, "kernel_initializer": {"class_name": "GlorotUniform", "config": {"seed": null}, "shared_object_id": 3}, "recurrent_initializer": {"class_name": "Orthogonal", "config": {"gain": 1.0, "seed": null}, "shared_object_id": 4}, "bias_initializer": {"class_name": "Zeros", "config": {}, "shared_object_id": 5}, "unit_forget_bias": true, "kernel_regularizer": null, "recurrent_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "recurrent_constraint": null, "bias_constraint": null, "dropout": 0.0, "recurrent_dropout": 0.0, "implementation": 2}, "name": "lstm", "inbound_nodes": [[["embedding", 0, 0, {}]]]}, {"class_name": "Dropout", "config": {"name": "dropout", "trainable": true, "dtype": "float32", "rate": 0.5, "noise_shape": null, "seed": null}, "name": "dropout", "inbound_nodes": [[["lstm", 0, 0, {}]]]}, {"class_name": "LSTM", "config": {"name": "lstm_1", "trainable": true, "dtype": 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"bias_constraint": null}, "name": "out_layer", "inbound_nodes": [[["dropout_1", 0, 0, {}]]]}, {"class_name": "Activation", "config": {"name": "activation", "trainable": true, "dtype": "float32", "activation": "sigmoid"}, "name": "activation", "inbound_nodes": [[["out_layer", 0, 0, {}]]]}], "input_layers": [["inputs", 0, 0]], "output_layers": [["activation", 0, 0]]}, "keras_version": "2.5.0", "backend": "tensorflow"} \ No newline at end of file diff --git a/nlp/models/acc82.49/tokenizer.json b/nlp/models/acc82.49/tokenizer.json new file mode 100644 index 0000000..fbe5971 --- /dev/null +++ b/nlp/models/acc82.49/tokenizer.json @@ -0,0 +1 @@ +"{\"class_name\": \"Tokenizer\", \"config\": {\"num_words\": 1000, \"filters\": \"!\\\"#$%&()*+,-./:;<=>?@[\\\\]^_`{|}~\\t\\n\", \"lower\": true, \"split\": \" \", \"char_level\": false, \"oov_token\": \"\", \"document_count\": 1028, \"word_counts\": \"{\\\"work\\\": 188, \\\"trying\\\": 46, \\\"give\\\": 3, \\\"something\\\": 41, \\\"funny\\\": 4, 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tensorflow.keras.layers import LSTM +from tensorflow.keras.models import Model # Define RNN Architecture def RNN(max_seq_len, vocab_size): diff --git a/nlp/train.py b/nlp/train.py index 235e189..f3344bd 100644 --- a/nlp/train.py +++ b/nlp/train.py @@ -8,11 +8,11 @@ import datetime # -- Deep Learning Libraries -- -from keras.callbacks import EarlyStopping -from keras.optimizers import RMSprop -from keras.preprocessing import sequence -from keras.preprocessing.text import Tokenizer -from keras.utils import to_categorical +from tensorflow.keras.callbacks import EarlyStopping +from tensorflow.keras.optimizers import RMSprop +from tensorflow.keras.preprocessing import sequence +from tensorflow.keras.preprocessing.text import Tokenizer +from tensorflow.keras.utils import to_categorical from sklearn.model_selection import train_test_split from sklearn.preprocessing import LabelEncoder

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