| ---
|
| 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-ner2-950
|
| 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-ner2-950 |
|
|
| 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: 0.1890 |
| - Precision: 0.8178 |
| - Recall: 0.8835 |
| - F1: 0.8494 |
|
|
| ## 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 | 119 | 0.1957 | 0.7993 | 0.8635 | 0.8301 | |
| | No log | 2.0 | 238 | 0.2062 | 0.7824 | 0.8735 | 0.8254 | |
| | No log | 3.0 | 357 | 0.1961 | 0.8004 | 0.8775 | 0.8372 | |
| | No log | 4.0 | 476 | 0.1922 | 0.8070 | 0.8815 | 0.8426 | |
| | 0.4283 | 5.0 | 595 | 0.1890 | 0.8178 | 0.8835 | 0.8494 | |
| | 0.4283 | 6.0 | 714 | 0.1985 | 0.8007 | 0.8956 | 0.8455 | |
| | 0.4283 | 7.0 | 833 | 0.1982 | 0.7943 | 0.8916 | 0.8401 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.15.2 |
| - Transformers 4.51.3 |
| - Pytorch 2.7.0+cu128 |
| - Datasets 3.5.0 |
| - Tokenizers 0.21.1 |
