| ---
|
| 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-ner2-650
|
| 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-ner2-650 |
|
|
| 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: 0.2844 |
| - Precision: 0.6701 |
| - Recall: 0.7871 |
| - F1: 0.7239 |
|
|
| ## 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 | 82 | 0.3143 | 0.6285 | 0.7610 | 0.6885 | |
| | No log | 2.0 | 164 | 0.3069 | 0.6459 | 0.7691 | 0.7021 | |
| | No log | 3.0 | 246 | 0.2976 | 0.6525 | 0.7691 | 0.7060 | |
| | No log | 4.0 | 328 | 0.2903 | 0.6672 | 0.7771 | 0.7180 | |
| | No log | 5.0 | 410 | 0.2978 | 0.6454 | 0.7932 | 0.7117 | |
| | No log | 6.0 | 492 | 0.2844 | 0.6701 | 0.7871 | 0.7239 | |
| | 0.6003 | 7.0 | 574 | 0.2880 | 0.6616 | 0.7892 | 0.7198 | |
| | 0.6003 | 8.0 | 656 | 0.2809 | 0.6638 | 0.7851 | 0.7194 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.15.2 |
| - Transformers 4.51.3 |
| - Pytorch 2.7.0+cu128 |
| - Datasets 3.5.0 |
| - Tokenizers 0.21.1 |
