---
library_name: peft
base_model: DeepPavlov/rubert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: pollen-ner-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-ner-2000

This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2712
- Precision: 0.7229
- Recall: 0.8434
- F1: 0.7785

## 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  | 0.7862          | 0.4691    | 0.0763 | 0.1313 |
| 1.1314        | 2.0   | 500  | 0.5175          | 0.4883    | 0.6305 | 0.5504 |
| 1.1314        | 3.0   | 750  | 0.4163          | 0.5199    | 0.7088 | 0.5998 |
| 0.6496        | 4.0   | 1000 | 0.3507          | 0.5949    | 0.7550 | 0.6655 |
| 0.6496        | 5.0   | 1250 | 0.3229          | 0.6238    | 0.7791 | 0.6929 |
| 0.51          | 6.0   | 1500 | 0.2990          | 0.6857    | 0.8193 | 0.7466 |
| 0.51          | 7.0   | 1750 | 0.2847          | 0.7075    | 0.8353 | 0.7661 |
| 0.4533        | 8.0   | 2000 | 0.2749          | 0.7133    | 0.8394 | 0.7712 |
| 0.4533        | 9.0   | 2250 | 0.2723          | 0.7216    | 0.8434 | 0.7778 |
| 0.4361        | 10.0  | 2500 | 0.2712          | 0.7229    | 0.8434 | 0.7785 |


### Framework versions

- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.7.0+cu128
- Datasets 3.5.0
- Tokenizers 0.21.1