| ---
|
| 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-ner2-600
|
| 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-ner2-600 |
|
|
| 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: 0.3100 |
| - Precision: 0.6451 |
| - Recall: 0.7590 |
| - F1: 0.6974 |
|
|
| ## 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 | 75 | 0.3387 | 0.6186 | 0.7329 | 0.6710 | |
| | No log | 2.0 | 150 | 0.3311 | 0.6181 | 0.7410 | 0.6740 | |
| | No log | 3.0 | 225 | 0.3248 | 0.6336 | 0.7430 | 0.6839 | |
| | No log | 4.0 | 300 | 0.3310 | 0.6120 | 0.7570 | 0.6768 | |
| | No log | 5.0 | 375 | 0.3218 | 0.6326 | 0.7570 | 0.6892 | |
| | No log | 6.0 | 450 | 0.3154 | 0.6342 | 0.7590 | 0.6910 | |
| | 0.65 | 7.0 | 525 | 0.3154 | 0.6332 | 0.7590 | 0.6904 | |
| | 0.65 | 8.0 | 600 | 0.3125 | 0.6396 | 0.7590 | 0.6942 | |
| | 0.65 | 9.0 | 675 | 0.3085 | 0.6449 | 0.7550 | 0.6957 | |
| | 0.65 | 10.0 | 750 | 0.3100 | 0.6451 | 0.7590 | 0.6974 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.15.2 |
| - Transformers 4.51.3 |
| - Pytorch 2.7.0+cu128 |
| - Datasets 3.5.0 |
| - Tokenizers 0.21.1 |
