---
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