--- license: apache-2.0 tags: - generated_from_trainer metrics: - accuracy - f1 model-index: - name: olm-bert-tiny-december-2022-target-glue-qqp results: [] --- # olm-bert-tiny-december-2022-target-glue-qqp This model is a fine-tuned version of [muhtasham/olm-bert-tiny-december-2022](https://huggingface.co/muhtasham/olm-bert-tiny-december-2022) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.5217 - Accuracy: 0.7433 - F1: 0.6048 ## 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: 3e-05 - train_batch_size: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: constant - training_steps: 5000 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| | 0.6283 | 0.04 | 500 | 0.5955 | 0.6795 | 0.5186 | | 0.5875 | 0.09 | 1000 | 0.5763 | 0.6972 | 0.5596 | | 0.5791 | 0.13 | 1500 | 0.5690 | 0.6975 | 0.6011 | | 0.5666 | 0.18 | 2000 | 0.5536 | 0.7156 | 0.5520 | | 0.5568 | 0.22 | 2500 | 0.5447 | 0.7230 | 0.5709 | | 0.5489 | 0.26 | 3000 | 0.5386 | 0.7281 | 0.5665 | | 0.5465 | 0.31 | 3500 | 0.5305 | 0.7329 | 0.5917 | | 0.5384 | 0.35 | 4000 | 0.5262 | 0.7357 | 0.6231 | | 0.5422 | 0.4 | 4500 | 0.5207 | 0.7409 | 0.6200 | | 0.5299 | 0.44 | 5000 | 0.5217 | 0.7433 | 0.6048 | ### Framework versions - Transformers 4.27.0.dev0 - Pytorch 1.13.1+cu116 - Datasets 2.9.1.dev0 - Tokenizers 0.13.2