pytorch jax bert text-classification transformers
.gitattributes README.md config.json flax_model.msgpack pytorch_model.bin special_tokens_map.json tokenizer_config.json training_args.bin vocab.txt
# BERT-IMDB

## What is it?
BERT (`bert-large-cased`) trained for sentiment classification on the [IMDB dataset](https://www.kaggle.com/lakshmi25npathi/imdb-dataset-of-50k-movie-reviews).

## Training setting

The model was trained on 80% of the IMDB dataset for sentiment classification for three epochs with a learning rate of `1e-5` with the `simpletransformers` library. The library uses a learning rate schedule.

## Result
The model achieved 90% classification accuracy on the validation set.

## Reference
The full experiment is available in the [tlr repo](https://lvwerra.github.io/trl/03-bert-imdb-training/).
