--- license: apache-2.0 tags: - generated_from_trainer datasets: - enoriega/odinsynth_dataset model-index: - name: rule_learning_margin_test results: [] --- # rule_learning_margin_test This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the enoriega/odinsynth_dataset dataset. It achieves the following results on the evaluation set: - Loss: 0.4104 ## 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: 4 - eval_batch_size: 4 - seed: 42 - gradient_accumulation_steps: 2000 - total_train_batch_size: 8000 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 3.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | |:-------------:|:-----:|:----:|:---------------:| | 0.6468 | 0.32 | 20 | 0.6191 | | 0.5185 | 0.64 | 40 | 0.5083 | | 0.459 | 0.96 | 60 | 0.4521 | | 0.4352 | 1.29 | 80 | 0.4192 | | 0.4427 | 1.61 | 100 | 0.4199 | | 0.4246 | 1.93 | 120 | 0.4131 | | 0.4301 | 2.26 | 140 | 0.4104 | | 0.428 | 2.58 | 160 | 0.4099 | | 0.4161 | 2.9 | 180 | 0.4102 | ### Framework versions - Transformers 4.19.2 - Pytorch 1.11.0 - Datasets 2.2.1 - Tokenizers 0.12.1