--- library_name: transformers license: cc-by-4.0 base_model: Goader/liberta-large tags: - generated_from_trainer datasets: - universal_dependencies metrics: - precision - recall - f1 - accuracy model-index: - name: liberta-large-upos results: - task: name: Token Classification type: token-classification dataset: name: universal_dependencies type: universal_dependencies config: uk_iu split: validation args: uk_iu metrics: - name: Precision type: precision value: 0.8100632457506624 - name: Recall type: recall value: 0.7466487546768732 - name: F1 type: f1 value: 0.7541998712736135 - name: Accuracy type: accuracy value: 0.8675486133248327 --- # liberta-large-upos This model is a fine-tuned version of [Goader/liberta-large](https://huggingface.co/Goader/liberta-large) on the universal_dependencies dataset. It achieves the following results on the evaluation set: - Loss: 0.3346 - Precision: 0.8101 - Recall: 0.7466 - F1: 0.7542 - Accuracy: 0.8675 ## 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=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| | No log | 1.0 | 338 | 1.0412 | 0.5939 | 0.4306 | 0.4617 | 0.5790 | | No log | 2.0 | 676 | 0.6850 | 0.6114 | 0.5788 | 0.5745 | 0.7115 | | No log | 3.0 | 1014 | 0.6075 | 0.6787 | 0.6205 | 0.6241 | 0.7389 | | No log | 4.0 | 1352 | 0.5585 | 0.7178 | 0.6393 | 0.6425 | 0.7608 | | No log | 5.0 | 1690 | 0.4762 | 0.7424 | 0.6737 | 0.6874 | 0.7984 | | No log | 6.0 | 2028 | 0.4203 | 0.7159 | 0.6962 | 0.6946 | 0.8228 | | No log | 7.0 | 2366 | 0.4275 | 0.7403 | 0.7081 | 0.7028 | 0.8205 | | No log | 8.0 | 2704 | 0.3789 | 0.7909 | 0.7189 | 0.7282 | 0.8470 | | No log | 9.0 | 3042 | 0.3431 | 0.8051 | 0.7415 | 0.7484 | 0.8626 | | No log | 10.0 | 3380 | 0.3346 | 0.8101 | 0.7466 | 0.7542 | 0.8675 | ### Framework versions - Transformers 4.44.2 - Pytorch 2.4.1+cu121 - Datasets 3.0.1 - Tokenizers 0.19.1