---
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