Updated README.md

README.md

@@ -12,7 +12,7 @@ widget:
 ## Javanese GPT-2 Small IMDB Classifier
 Javanese GPT-2 Small IMDB Classifier is a movie-classification model based on the [GPT-2 model](https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf). It was trained on Javanese IMDB movie reviews.
 
-The model was originally [`w11wo/javanese-gpt2-small-imdb`](https://huggingface.co/w11wo/javanese-gpt2-small-imdb) which is then fine-tuned on the [`w11wo/imdb-javanese`](https://huggingface.co/datasets/w11wo/imdb-javanese) dataset consisting of Javanese IMDB movie reviews. It achieved an accuracy of 77.18% on the validation dataset. Many of the techniques used are based on a Hugging Face tutorial [notebook](https://github.com/huggingface/notebooks/blob/master/examples/text_classification.ipynb) written by [Sylvain Gugger](https://github.com/sgugger).
+The model was originally [`w11wo/javanese-gpt2-small-imdb`](https://huggingface.co/w11wo/javanese-gpt2-small-imdb) which is then fine-tuned on the [`w11wo/imdb-javanese`](https://huggingface.co/datasets/w11wo/imdb-javanese) dataset consisting of Javanese IMDB movie reviews. It achieved an accuracy of 76.70% on the validation dataset. Many of the techniques used are based on a Hugging Face tutorial [notebook](https://github.com/huggingface/notebooks/blob/master/examples/text_classification.ipynb) written by [Sylvain Gugger](https://github.com/sgugger).
 
 Hugging Face's `Trainer` class from the [Transformers]((https://huggingface.co/transformers)) library was used to train the model. PyTorch was used as the backend framework during training, but the model remains compatible with TensorFlow nonetheless.
 
@@ -26,7 +26,7 @@ The model was trained for 5 epochs and the following is the final result once th
 
 | train loss | valid loss |  accuracy  | total time  |
 |------------|------------|------------|-------------|
-|    0.279   |    0.622   |   0.771    |   1:31:25   |
+|    0.324   |    0.574   |   0.767    |   2:0:14    |
 
 ## How to Use
 ### As Text Classifier