--- library_name: peft base_model: DeepPavlov/bert-base-bg-cs-pl-ru-cased tags: - generated_from_trainer metrics: - precision - recall - f1 model-index: - name: pollen-ner2-1900 results: [] --- # pollen-ner2-1900 This model is a fine-tuned version of [DeepPavlov/bert-base-bg-cs-pl-ru-cased](https://huggingface.co/DeepPavlov/bert-base-bg-cs-pl-ru-cased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1668 - Precision: 0.8434 - Recall: 0.8976 - F1: 0.8696 ## 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: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Use OptimizerNames.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: 10 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:| | No log | 1.0 | 238 | 0.1668 | 0.8434 | 0.8976 | 0.8696 | | No log | 2.0 | 476 | 0.1640 | 0.8330 | 0.8916 | 0.8613 | | 0.2462 | 3.0 | 714 | 0.1634 | 0.8409 | 0.8916 | 0.8655 | ### Framework versions - PEFT 0.15.2 - Transformers 4.51.3 - Pytorch 2.7.0+cu128 - Datasets 3.5.0 - Tokenizers 0.21.1