--- library_name: transformers language: - en base_model: gokulsrinivasagan/bert_tiny_lda_20_v1_book tags: - generated_from_trainer datasets: - glue metrics: - accuracy model-index: - name: bert_tiny_lda_20_v1_book_rte results: - task: name: Text Classification type: text-classification dataset: name: GLUE RTE type: glue args: rte metrics: - name: Accuracy type: accuracy value: 0.5342960288808665 --- # bert_tiny_lda_20_v1_book_rte This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_20_v1_book](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_20_v1_book) on the GLUE RTE dataset. It achieves the following results on the evaluation set: - Loss: 0.6854 - Accuracy: 0.5343 ## 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:| | 0.7071 | 1.0 | 10 | 0.6985 | 0.4693 | | 0.6942 | 2.0 | 20 | 0.6904 | 0.5487 | | 0.6872 | 3.0 | 30 | 0.6893 | 0.5379 | | 0.6791 | 4.0 | 40 | 0.6854 | 0.5343 | | 0.6633 | 5.0 | 50 | 0.7277 | 0.5523 | | 0.6418 | 6.0 | 60 | 0.6989 | 0.5415 | | 0.5818 | 7.0 | 70 | 0.7711 | 0.5379 | | 0.5207 | 8.0 | 80 | 0.7769 | 0.5596 | | 0.419 | 9.0 | 90 | 0.8660 | 0.5307 | ### Framework versions - Transformers 4.46.3 - Pytorch 2.2.1+cu118 - Datasets 2.17.0 - Tokenizers 0.20.3