Instructions to use DanielNRU/pollen-ner2-1350 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use DanielNRU/pollen-ner2-1350 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-ner2-1350") - Notebooks
- Google Colab
- Kaggle
pollen-ner2-1350
This model is a fine-tuned version of DeepPavlov/bert-base-bg-cs-pl-ru-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1532
- Precision: 0.8377
- Recall: 0.9016
- F1: 0.8685
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 | 169 | 0.1732 | 0.8141 | 0.9056 | 0.8574 |
| No log | 2.0 | 338 | 0.1638 | 0.8272 | 0.9036 | 0.8637 |
| 0.3331 | 3.0 | 507 | 0.1532 | 0.8377 | 0.9016 | 0.8685 |
| 0.3331 | 4.0 | 676 | 0.1514 | 0.8402 | 0.8976 | 0.8680 |
| 0.3331 | 5.0 | 845 | 0.1584 | 0.8349 | 0.9036 | 0.8679 |
Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.5.0
- Tokenizers 0.21.1
- Downloads last month
- 1
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for DanielNRU/pollen-ner2-1350
Base model
DeepPavlov/bert-base-bg-cs-pl-ru-cased