| ---
|
| 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-ner2-2000
|
| 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-ner2-2000 |
|
|
| 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: 0.8899 |
| - Precision: 0.4765 |
| - Recall: 0.3454 |
| - F1: 0.4005 |
|
|
| ## 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 | 250 | 1.0836 | 0.0 | 0.0 | 0.0 | |
| | 1.3679 | 2.0 | 500 | 1.0371 | 0.5155 | 0.1004 | 0.1681 | |
| | 1.3679 | 3.0 | 750 | 0.9841 | 0.52 | 0.1566 | 0.2407 | |
| | 1.2071 | 4.0 | 1000 | 0.9465 | 0.4964 | 0.2731 | 0.3523 | |
| | 1.2071 | 5.0 | 1250 | 0.9209 | 0.4878 | 0.2811 | 0.3567 | |
| | 1.126 | 6.0 | 1500 | 0.9238 | 0.4780 | 0.3052 | 0.3725 | |
| | 1.126 | 7.0 | 1750 | 0.8950 | 0.4814 | 0.3112 | 0.3780 | |
| | 1.0828 | 8.0 | 2000 | 0.8930 | 0.4701 | 0.3313 | 0.3887 | |
| | 1.0828 | 9.0 | 2250 | 0.8923 | 0.4737 | 0.3434 | 0.3981 | |
| | 1.0658 | 10.0 | 2500 | 0.8899 | 0.4765 | 0.3454 | 0.4005 | |
|
|
|
|
| ### Framework versions |
|
|
| - PEFT 0.15.2 |
| - Transformers 4.51.3 |
| - Pytorch 2.7.0+cu128 |
| - Datasets 3.5.0 |
| - Tokenizers 0.21.1 |
