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

# ruRoberta-large_ner

This model is a fine-tuned version of [ai-forever/ruRoberta-large](https://huggingface.co/ai-forever/ruRoberta-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0824
- Precision: 0.7879
- Recall: 0.8667
- F1: 0.8254
- Accuracy: 0.9667

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 15   | 0.2732          | 0.5833    | 0.7    | 0.6364 | 0.88     |
| No log        | 2.0   | 30   | 0.1424          | 0.7059    | 0.8    | 0.7500 | 0.94     |
| No log        | 3.0   | 45   | 0.0824          | 0.7879    | 0.8667 | 0.8254 | 0.9667   |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0.dev20230621+cu117
- Datasets 2.13.0
- Tokenizers 0.13.3