Modelpublic

michelecafagna26/gpt2-medium-finetuned-sst2-sentiment

sourceHugging Faceapache-2.0updated 3y agoView on Hugging Face

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Model Card

GPT-2-medium fine-tuned for Sentiment Analysis 👍👎

OpenAI's GPT-2 medium fine-tuned on SST-2 dataset for Sentiment Analysis downstream task.

Details of GPT-2

The GPT-2 model was presented in Language Models are Unsupervised Multitask Learners by Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever

Model fine-tuning 🏋️‍

The model has been finetuned for 10 epochs on standard hyperparameters

Val set metrics 🧾

precision	recall	f1-score	support
negative	0.92	0.92	0.92	428
positive	0.92	0.93	0.92	444
----------	----------	---------	----------	-------
accuracy			0.92	872
macro avg	0.92	0.92	0.92	872
weighted avg	0.92	0.92	0.92	872

Model in Action 🚀

python

from transformers import GPT2Tokenizer, GPT2ForSequenceClassification

tokenizer = GPT2Tokenizer.from_pretrained("michelecafagna26/gpt2-medium-finetuned-sst2-sentiment")
model = GPT2ForSequenceClassification.from_pretrained("michelecafagna26/gpt2-medium-finetuned-sst2-sentiment")

inputs = tokenizer("I love it", return_tensors="pt")

model(**inputs).logits.argmax(axis=1)

# 1: Positive, 0: Negative
# Output: tensor([1])

This model card is based on "mrm8488/t5-base-finetuned-imdb-sentiment" by Manuel Romero/@mrm8488