--- license: apache-2.0 base_model: albert-base-v2 tags: - generated_from_trainer datasets: - squad model-index: - name: albert-base-qa-1-lr-1 results: [] --- # albert-base-qa-1-lr-1 This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on the squad dataset. It achieves the following results on the evaluation set: - Loss: 0.8908 ## 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: 1e-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: 2 ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.8674 | 1.0 | 3942 | 0.8352 | | 0.5593 | 2.0 | 7884 | 0.8908 | ### Framework versions - Transformers 4.34.1 - Pytorch 2.1.0+cu118 - Datasets 2.14.5 - Tokenizers 0.14.1