--- language: - en license: apache-2.0 base_model: JackFram/llama-160m tags: - generated_from_trainer datasets: - glue metrics: - accuracy model-index: - name: llama-160m-qnli results: - task: name: Text Classification type: text-classification dataset: name: GLUE QNLI type: glue args: qnli metrics: - name: Accuracy type: accuracy value: 0.5149185429251327 --- # llama-160m-qnli This model is a fine-tuned version of [JackFram/llama-160m](https://huggingface.co/JackFram/llama-160m) on the GLUE QNLI dataset. It achieves the following results on the evaluation set: - Loss: 0.8172 - Accuracy: 0.5149 ## 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: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5.0 ### Training results ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu117 - Datasets 2.18.0 - Tokenizers 0.13.3