metadata

language:
  - en
license: apache-2.0
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: gpt2-finetuned-qnli
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE QNLI
          type: glue
          args: qnli
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.87791

gpt2-finetuned-qnli

This model is GPT-2 fine-tuned on GLUE STS-B dataset. It acheives the following results on the validation set

Accuracy: 0.87791

Model Details

GPT-2 is a transformers model pretrained on a very large corpus of English data in a self-supervised fashion. This means it was pretrained on the raw texts only, with no humans labelling them in any way (which is why it can use lots of publicly available data) with an automatic process to generate inputs and labels from those texts. More precisely, it was trained to guess the next word in sentences. However, it acheives very good results on Text Classification tasks.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-5
train_batch_size: 8
eval_batch_size: 8
seed: 123
optimizer: epsilon=1e-08
num_epochs: 3

Training results

Epoch	Training Loss	Training Accuracy	Validation Loss	Validation Accuracy
1	0.47803	0.77344	0.34630	0.85502
2	0.36961	0.85486	0.32994	0.85502
3	0.32343	0.88785	0.38374	0.87791