--- license: mit base_model: openai-community/gpt2-large tags: - generated_from_trainer datasets: - stanfordnlp/snli metrics: - accuracy model-index: - name: gpt2-large-bn-adapter-7.42M-snli-model1 results: - task: name: Text Classification type: text-classification dataset: name: snli type: stanfordnlp/snli metrics: - name: Accuracy type: accuracy value: 0.9016460069091649 --- # gpt2-large-bn-adapter-7.42M-snli-model1 This model is a fine-tuned version of [openai-community/gpt2-large](https://huggingface.co./openai-community/gpt2-large) on the snli dataset. It achieves the following results on the evaluation set: - Loss: 0.2719 - Accuracy: 0.9016 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 2e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 2 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.3654 | 1.0 | 17168 | 0.3073 | 0.8859 | | 0.3239 | 2.0 | 34336 | 0.2859 | 0.8967 | | 0.3041 | 3.0 | 51504 | 0.2719 | 0.9016 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.1+cu121 - Datasets 2.15.0 - Tokenizers 0.15.0