Instructions to use DanielNRU/pollen-ner2-50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DanielNRU/pollen-ner2-50 with PEFT:
from peft import PeftModel from transformers import AutoModelForTokenClassification base_model = AutoModelForTokenClassification.from_pretrained("DeepPavlov/bert-base-bg-cs-pl-ru-cased") model = PeftModel.from_pretrained(base_model, "DanielNRU/pollen-ner2-50") - Notebooks
- Google Colab
- Kaggle
| 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-ner2-50 | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # pollen-ner2-50 | |
| 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: 2.2569 | |
| - Precision: 0.0107 | |
| - Recall: 0.0582 | |
| - F1: 0.0181 | |
| ## 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 | 7 | 2.2569 | 0.0107 | 0.0582 | 0.0181 | | |
| | No log | 2.0 | 14 | 2.1452 | 0.0104 | 0.0422 | 0.0166 | | |
| | No log | 3.0 | 21 | 2.0358 | 0.0054 | 0.0141 | 0.0078 | | |
| ### Framework versions | |
| - PEFT 0.15.2 | |
| - Transformers 4.51.3 | |
| - Pytorch 2.7.0+cu128 | |
| - Datasets 3.5.0 | |
| - Tokenizers 0.21.1 |