--- library_name: peft base_model: DeepPavlov/rubert-base-cased tags: - generated_from_trainer metrics: - precision - recall - f1 model-index: - name: pollen-ner-2000 results: [] --- # pollen-ner-2000 This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.1544 - Precision: 0.8772 - Recall: 0.9177 - F1: 0.8970 ## 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 | 250 | 0.1490 | 0.8738 | 0.9177 | 0.8952 | | 0.1571 | 2.0 | 500 | 0.1544 | 0.8772 | 0.9177 | 0.8970 | | 0.1571 | 3.0 | 750 | 0.1536 | 0.8738 | 0.9177 | 0.8952 | | 0.1537 | 4.0 | 1000 | 0.1531 | 0.8714 | 0.9116 | 0.8911 | ### Framework versions - PEFT 0.15.2 - Transformers 4.51.3 - Pytorch 2.7.0+cu128 - Datasets 3.5.0 - Tokenizers 0.21.1