---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- collection3
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: rubert-finetuned-collection3
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: collection3
      type: collection3
      config: default
      split: train
      args: default
    metrics:
    - name: Precision
      type: precision
      value: 0.9354685646500593
    - name: Recall
      type: recall
      value: 0.9577362156910372
    - name: F1
      type: f1
      value: 0.9464714354296688
    - name: Accuracy
      type: accuracy
      value: 0.986481047855993
---

<!-- 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-finetuned-collection3

This model is a fine-tuned version of [sberbank-ai/ruBert-base](https://huggingface.co/sberbank-ai/ruBert-base) on the collection3 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0514
- Precision: 0.9355
- Recall: 0.9577
- F1: 0.9465
- Accuracy: 0.9865

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0794        | 1.0   | 1163 | 0.0536          | 0.9178    | 0.9466 | 0.9320 | 0.9825   |
| 0.0391        | 2.0   | 2326 | 0.0512          | 0.9228    | 0.9553 | 0.9388 | 0.9853   |
| 0.0191        | 3.0   | 3489 | 0.0514          | 0.9355    | 0.9577 | 0.9465 | 0.9865   |


### Framework versions

- Transformers 4.25.1
- Pytorch 1.13.0.dev20220929+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2