--- library_name: transformers language: - en base_model: gokulsrinivasagan/bert_base_lda_5_v1_book tags: - generated_from_trainer datasets: - glue metrics: - accuracy - f1 model-index: - name: bert_base_lda_5_v1_book_qqp results: - task: name: Text Classification type: text-classification dataset: name: GLUE QQP type: glue args: qqp metrics: - name: Accuracy type: accuracy value: 0.883007667573584 - name: F1 type: f1 value: 0.8522613693153424 --- # bert_base_lda_5_v1_book_qqp This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_5_v1_book](https://huggingface.co/gokulsrinivasagan/bert_base_lda_5_v1_book) on the GLUE QQP dataset. It achieves the following results on the evaluation set: - Loss: 0.2715 - Accuracy: 0.8830 - F1: 0.8523 - Combined Score: 0.8676 ## 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: 5e-05 - train_batch_size: 256 - eval_batch_size: 256 - seed: 10 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - num_epochs: 50 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Combined Score | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:| | 0.3439 | 1.0 | 1422 | 0.2776 | 0.8779 | 0.8319 | 0.8549 | | 0.2315 | 2.0 | 2844 | 0.2715 | 0.8830 | 0.8523 | 0.8676 | | 0.1614 | 3.0 | 4266 | 0.2738 | 0.8950 | 0.8622 | 0.8786 | | 0.1118 | 4.0 | 5688 | 0.3073 | 0.8937 | 0.8585 | 0.8761 | | 0.0815 | 5.0 | 7110 | 0.3470 | 0.8996 | 0.8653 | 0.8825 | | 0.0631 | 6.0 | 8532 | 0.3771 | 0.8963 | 0.8636 | 0.8800 | | 0.0515 | 7.0 | 9954 | 0.3934 | 0.8972 | 0.8633 | 0.8802 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.2.1+cu118 - Datasets 2.17.0 - Tokenizers 0.20.3