---
base_model: ai-forever/ruBert-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ruBert-large_ner
  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. -->

# ruBert-large_ner

This model is a fine-tuned version of [ai-forever/ruBert-large](https://huggingface.co/ai-forever/ruBert-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5158
- Precision: 0.8832
- Recall: 0.9014
- F1: 0.8912
- Accuracy: 0.9234

## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 438  | 0.3216          | 0.8700    | 0.8309 | 0.8448 | 0.8941   |
| 0.3915        | 2.0   | 876  | 0.3379          | 0.8596    | 0.8790 | 0.8672 | 0.9089   |
| 0.175         | 3.0   | 1314 | 0.3441          | 0.8656    | 0.8833 | 0.8737 | 0.9092   |
| 0.0942        | 4.0   | 1752 | 0.3751          | 0.8651    | 0.8856 | 0.8729 | 0.9104   |
| 0.0597        | 5.0   | 2190 | 0.3919          | 0.8881    | 0.9002 | 0.8935 | 0.9236   |
| 0.0309        | 6.0   | 2628 | 0.4360          | 0.8730    | 0.8958 | 0.8821 | 0.9171   |
| 0.0154        | 7.0   | 3066 | 0.4564          | 0.8848    | 0.8985 | 0.8907 | 0.9234   |
| 0.0064        | 8.0   | 3504 | 0.4809          | 0.8797    | 0.9036 | 0.8904 | 0.9236   |
| 0.0064        | 9.0   | 3942 | 0.5027          | 0.8832    | 0.9024 | 0.8917 | 0.9232   |
| 0.0024        | 10.0  | 4380 | 0.5158          | 0.8832    | 0.9014 | 0.8912 | 0.9234   |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1