metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - imdb
metrics:
  - accuracy
model-index:
  - name: gpt2-imdb-sentiment-classifier
    results:
      - task:
          name: Text Classification
          type: text-classification
        dataset:
          name: imdb
          type: imdb
          args: plain_text
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.9394

gpt2-imdb-sentiment-classifier

This model is a fine-tuned version of gpt2 on the imdb dataset. It achieves the following results on the evaluation set:

Loss: 0.1703
Accuracy: 0.9394

Model description

More information needed

Intended uses & limitations

This is comparable to distilbert-imdb and trained with exactly the same script

It achieves slightly lower loss (0.1703 vs 0.1903) and slightly higher accuracy (0.9394 vs 0.928)

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 5e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1967	1.0	1563	0.1703	0.9394

Framework versions

Transformers 4.18.0
Pytorch 1.13.1+cu117
Datasets 2.9.0
Tokenizers 0.12.1