metadata

language:
  - en
license: apache-2.0
datasets:
  - glue
metrics:
  - accuracy
model-index:
  - name: gpt2-finetuned-rte
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: GLUE RTE
          type: glue
          args: rte
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.52347

gpt2-finetuned-rte

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

Accuracy: 0.52347

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: 16
eval_batch_size: 16
seed: 123
optimizer: epsilon=1e-08
num_epochs: 3

Training results

Epoch	Training Loss	Training Accuracy	Validation Loss	Validation Accuracy
1	0.70926	0.50482	0.69049	0.51986
2	0.69589	0.53173	0.69589	0.52347
3	0.68842	0.53454	0.70151	0.51986