--- license: mit tags: - generated_from_trainer model-index: - name: rubert-tiny2-srl results: [] --- # rubert-tiny2-srl This model is a fine-tuned version of [cointegrated/rubert-tiny2](https://huggingface.co/cointegrated/rubert-tiny2) on an unknown dataset. It achieves the following results on the evaluation set: - eval_loss: 0.4175 - eval_Benefactive_precision: 0.0 - eval_Benefactive_recall: 0.0 - eval_Benefactive_f1: 0.0 - eval_Benefactive_number: 5 - eval_Causator_precision: 0.0 - eval_Causator_recall: 0.0 - eval_Causator_f1: 0.0 - eval_Causator_number: 26 - eval_Cause_precision: 0.0 - eval_Cause_recall: 0.0 - eval_Cause_f1: 0.0 - eval_Cause_number: 21 - eval_ContrSubject_precision: 0.0 - eval_ContrSubject_recall: 0.0 - eval_ContrSubject_f1: 0.0 - eval_ContrSubject_number: 19 - eval_Deliberative_precision: 0.0 - eval_Deliberative_recall: 0.0 - eval_Deliberative_f1: 0.0 - eval_Deliberative_number: 10 - eval_Experiencer_precision: 0.5512 - eval_Experiencer_recall: 0.4321 - eval_Experiencer_f1: 0.4844 - eval_Experiencer_number: 162 - eval_Object_precision: 0.6905 - eval_Object_recall: 0.0963 - eval_Object_f1: 0.1691 - eval_Object_number: 301 - eval_Predicate_precision: 0.9360 - eval_Predicate_recall: 0.9737 - eval_Predicate_f1: 0.9545 - eval_Predicate_number: 571 - eval_overall_precision: 0.8585 - eval_overall_recall: 0.5874 - eval_overall_f1: 0.6976 - eval_overall_accuracy: 0.8855 - eval_runtime: 1.6021 - eval_samples_per_second: 355.786 - eval_steps_per_second: 355.786 - epoch: 1.0 - step: 4864 ## 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: 1.1643470912014148e-05 - train_batch_size: 1 - eval_batch_size: 1 - seed: 163748 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.28 - num_epochs: 5 - mixed_precision_training: Native AMP ### Framework versions - Transformers 4.28.1 - Pytorch 2.0.0+cu117 - Datasets 2.11.0 - Tokenizers 0.13.3