--- tags: - generated_from_trainer model-index: - name: rubert-base-srl-seqlabeling results: [] --- # rubert-base-srl-seqlabeling This model is a fine-tuned version of [./ruBert-base/](https://huggingface.co/./ruBert-base/) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1723 - Causator Precision: 0.8539 - Causator Recall: 0.8352 - Causator F1: 0.8444 - Causator Number: 91 - Expiriencer Precision: 0.9259 - Expiriencer Recall: 0.9740 - Expiriencer F1: 0.9494 - Expiriencer Number: 77 - Instrument Precision: 0.375 - Instrument Recall: 1.0 - Instrument F1: 0.5455 - Instrument Number: 3 - Other Precision: 0.0 - Other Recall: 0.0 - Other F1: 0.0 - Other Number: 1 - Predicate Precision: 0.9352 - Predicate Recall: 0.9902 - Predicate F1: 0.9619 - Predicate Number: 102 - Overall Precision: 0.8916 - Overall Recall: 0.9307 - Overall F1: 0.9107 - Overall Accuracy: 0.9667 ## 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: 16 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.06 - num_epochs: 10.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Causator Precision | Causator Recall | Causator F1 | Causator Number | Expiriencer Precision | Expiriencer Recall | Expiriencer F1 | Expiriencer Number | Instrument Precision | Instrument Recall | Instrument F1 | Instrument Number | Other Precision | Other Recall | Other F1 | Other Number | Predicate Precision | Predicate Recall | Predicate F1 | Predicate Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | |:-------------:|:-----:|:----:|:---------------:|:------------------:|:---------------:|:-----------:|:---------------:|:---------------------:|:------------------:|:--------------:|:------------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:---------------:|:------------:|:--------:|:------------:|:-------------------:|:----------------:|:------------:|:----------------:|:-----------------:|:--------------:|:----------:|:----------------:| | 0.2552 | 1.0 | 56 | 0.3471 | 0.8841 | 0.6703 | 0.7625 | 91 | 0.8421 | 0.8312 | 0.8366 | 77 | 0.0 | 0.0 | 0.0 | 3 | 0.0 | 0.0 | 0.0 | 1 | 0.9259 | 0.9804 | 0.9524 | 102 | 0.8893 | 0.8212 | 0.8539 | 0.9203 | | 0.2385 | 2.0 | 112 | 0.1608 | 0.9103 | 0.7802 | 0.8402 | 91 | 0.9375 | 0.9740 | 0.9554 | 77 | 0.2857 | 0.6667 | 0.4 | 3 | 0.0 | 0.0 | 0.0 | 1 | 0.9519 | 0.9706 | 0.9612 | 102 | 0.9182 | 0.9015 | 0.9098 | 0.9554 | | 0.0367 | 3.0 | 168 | 0.1311 | 0.8902 | 0.8022 | 0.8439 | 91 | 0.9375 | 0.9740 | 0.9554 | 77 | 0.4286 | 1.0 | 0.6 | 3 | 0.0 | 0.0 | 0.0 | 1 | 0.9709 | 0.9804 | 0.9756 | 102 | 0.9228 | 0.9161 | 0.9194 | 0.9673 | | 0.0494 | 4.0 | 224 | 0.1507 | 0.7812 | 0.8242 | 0.8021 | 91 | 0.9241 | 0.9481 | 0.9359 | 77 | 0.4286 | 1.0 | 0.6 | 3 | 0.0 | 0.0 | 0.0 | 1 | 0.9524 | 0.9804 | 0.9662 | 102 | 0.8746 | 0.9161 | 0.8948 | 0.9637 | | 0.0699 | 5.0 | 280 | 0.1830 | 0.8276 | 0.7912 | 0.8090 | 91 | 0.8941 | 0.9870 | 0.9383 | 77 | 0.375 | 1.0 | 0.5455 | 3 | 0.0 | 0.0 | 0.0 | 1 | 0.9352 | 0.9902 | 0.9619 | 102 | 0.875 | 0.9197 | 0.8968 | 0.9560 | | 0.0352 | 6.0 | 336 | 0.1994 | 0.7857 | 0.8462 | 0.8148 | 91 | 0.9048 | 0.9870 | 0.9441 | 77 | 0.375 | 1.0 | 0.5455 | 3 | 0.0 | 0.0 | 0.0 | 1 | 0.9266 | 0.9902 | 0.9573 | 102 | 0.8595 | 0.9380 | 0.8970 | 0.9572 | | 0.0186 | 7.0 | 392 | 0.1657 | 0.8652 | 0.8462 | 0.8556 | 91 | 0.9146 | 0.9740 | 0.9434 | 77 | 0.375 | 1.0 | 0.5455 | 3 | 0.0 | 0.0 | 0.0 | 1 | 0.9352 | 0.9902 | 0.9619 | 102 | 0.8920 | 0.9343 | 0.9127 | 0.9673 | | 0.0052 | 8.0 | 448 | 0.1716 | 0.8556 | 0.8462 | 0.8508 | 91 | 0.9259 | 0.9740 | 0.9494 | 77 | 0.375 | 1.0 | 0.5455 | 3 | 0.0 | 0.0 | 0.0 | 1 | 0.9352 | 0.9902 | 0.9619 | 102 | 0.8920 | 0.9343 | 0.9127 | 0.9673 | | 0.0094 | 9.0 | 504 | 0.1715 | 0.8444 | 0.8352 | 0.8398 | 91 | 0.9259 | 0.9740 | 0.9494 | 77 | 0.4286 | 1.0 | 0.6 | 3 | 0.0 | 0.0 | 0.0 | 1 | 0.9352 | 0.9902 | 0.9619 | 102 | 0.8916 | 0.9307 | 0.9107 | 0.9667 | | 0.0078 | 10.0 | 560 | 0.1723 | 0.8539 | 0.8352 | 0.8444 | 91 | 0.9259 | 0.9740 | 0.9494 | 77 | 0.375 | 1.0 | 0.5455 | 3 | 0.0 | 0.0 | 0.0 | 1 | 0.9352 | 0.9902 | 0.9619 | 102 | 0.8916 | 0.9307 | 0.9107 | 0.9667 | ### Framework versions - Transformers 4.13.0.dev0 - Pytorch 1.10.0+cu102 - Datasets 1.15.1 - Tokenizers 0.10.3