---
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