# 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/).

{}
transformers pytorch jax bert text-classification autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #jax #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us 

# BERT-IMDB

## What is it?
BERT ('bert-large-cased') trained for sentiment classification on the IMDB dataset.

## 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.

# BERT-IMDB ## What is it?
BERT ('bert-large-cased') trained for sentiment classification on the IMDB dataset. ## 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.
TAGS
#transformers #pytorch #jax #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us 
 # BERT-IMDB ## What is it?
BERT ('bert-large-cased') trained for sentiment classification on the IMDB dataset. ## 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.
passage: TAGS
#transformers #pytorch #jax #bert #text-classification #autotrain_compatible #endpoints_compatible #region-us 
# BERT-IMDB## What is it?
BERT ('bert-large-cased') trained for sentiment classification on the IMDB dataset.## 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.