---
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