google-research-datasets/newsgroup
Updated • 983 • 10
How to use sumedh/pretrained-word-embeddings with Keras:
# !pip install -U keras tensorflow huggingface_hub
# Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here;
# "jax" and "torch" also work for computation once TensorFlow is installed.
import os
os.environ["KERAS_BACKEND"] = "tensorflow"
import keras
model = keras.saving.load_model("hf://sumedh/pretrained-word-embeddings")
Text classification on the Newsgroup20 dataset using pre-trained GloVe word embeddings.
This repo contains the model to this Keras example using pre-trained word embeddings.
Full credits to : fchollet
Model reproduced by : Sumedh
Newsgroup20 dataset, a set of 20,000 message board messages belonging to 20 different topic categories
The following hyperparameters were used during training:
| name | learning_rate | decay | rho | momentum | epsilon | centered | training_precision |
|---|---|---|---|---|---|---|---|
| RMSprop | 0.0010000000474974513 | 0.0 | 0.8999999761581421 | 0.0 | 1e-07 | False | float32 |