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

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: 0.5140
- Precision: 0.5566
- Recall: 0.5871
- F1: 0.5714
- Accuracy: 0.8981

## 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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 50   | 0.6582          | 0.0       | 0.0    | 0.0    | 0.7628   |
| No log        | 2.0   | 100  | 0.5705          | 0.0118    | 0.0173 | 0.0140 | 0.7783   |
| No log        | 3.0   | 150  | 0.4784          | 0.0277    | 0.0501 | 0.0356 | 0.8028   |
| No log        | 4.0   | 200  | 0.4043          | 0.0784    | 0.1329 | 0.0986 | 0.8323   |
| No log        | 5.0   | 250  | 0.3553          | 0.1545    | 0.2697 | 0.1965 | 0.8523   |
| No log        | 6.0   | 300  | 0.4051          | 0.2312    | 0.2601 | 0.2448 | 0.8692   |
| No log        | 7.0   | 350  | 0.3351          | 0.3456    | 0.3796 | 0.3618 | 0.8901   |
| No log        | 8.0   | 400  | 0.2774          | 0.3344    | 0.3911 | 0.3606 | 0.8974   |
| No log        | 9.0   | 450  | 0.3010          | 0.3819    | 0.5048 | 0.4349 | 0.9022   |
| 0.3753        | 10.0  | 500  | 0.2892          | 0.4114    | 0.4875 | 0.4462 | 0.9051   |
| 0.3753        | 11.0  | 550  | 0.2773          | 0.3707    | 0.5222 | 0.4336 | 0.9076   |
| 0.3753        | 12.0  | 600  | 0.3447          | 0.4706    | 0.5549 | 0.5093 | 0.9076   |
| 0.3753        | 13.0  | 650  | 0.3312          | 0.4317    | 0.5356 | 0.4781 | 0.9073   |
| 0.3753        | 14.0  | 700  | 0.2870          | 0.4818    | 0.6378 | 0.5489 | 0.9132   |
| 0.3753        | 15.0  | 750  | 0.3944          | 0.4443    | 0.5992 | 0.5103 | 0.9024   |
| 0.3753        | 16.0  | 800  | 0.3599          | 0.4319    | 0.6416 | 0.5163 | 0.9018   |
| 0.3753        | 17.0  | 850  | 0.3568          | 0.4560    | 0.6397 | 0.5325 | 0.9042   |
| 0.3753        | 18.0  | 900  | 0.4296          | 0.4674    | 0.5241 | 0.4941 | 0.9106   |
| 0.3753        | 19.0  | 950  | 0.3939          | 0.4617    | 0.5453 | 0.5    | 0.9137   |
| 0.0842        | 20.0  | 1000 | 0.3882          | 0.5109    | 0.5434 | 0.5266 | 0.9066   |
| 0.0842        | 21.0  | 1050 | 0.3870          | 0.5311    | 0.6243 | 0.5740 | 0.9075   |
| 0.0842        | 22.0  | 1100 | 0.4163          | 0.4252    | 0.6628 | 0.5181 | 0.8925   |
| 0.0842        | 23.0  | 1150 | 0.4097          | 0.4577    | 0.5010 | 0.4784 | 0.9004   |
| 0.0842        | 24.0  | 1200 | 0.3709          | 0.5482    | 0.6031 | 0.5743 | 0.9161   |
| 0.0842        | 25.0  | 1250 | 0.3366          | 0.5088    | 0.6647 | 0.5764 | 0.9141   |
| 0.0842        | 26.0  | 1300 | 0.4558          | 0.6132    | 0.6108 | 0.6120 | 0.9171   |
| 0.0842        | 27.0  | 1350 | 0.4982          | 0.5720    | 0.5896 | 0.5806 | 0.9102   |
| 0.0842        | 28.0  | 1400 | 0.3998          | 0.5615    | 0.6513 | 0.6030 | 0.9178   |
| 0.0842        | 29.0  | 1450 | 0.5028          | 0.5620    | 0.6551 | 0.6050 | 0.9108   |
| 0.0476        | 30.0  | 1500 | 0.3672          | 0.5739    | 0.6435 | 0.6067 | 0.9117   |
| 0.0476        | 31.0  | 1550 | 0.4520          | 0.5330    | 0.6532 | 0.5870 | 0.9084   |
| 0.0476        | 32.0  | 1600 | 0.5027          | 0.5628    | 0.6127 | 0.5867 | 0.9101   |
| 0.0476        | 33.0  | 1650 | 0.4461          | 0.4581    | 0.6108 | 0.5235 | 0.9087   |
| 0.0476        | 34.0  | 1700 | 0.4407          | 0.4726    | 0.5992 | 0.5285 | 0.9070   |
| 0.0476        | 35.0  | 1750 | 0.4512          | 0.5211    | 0.5241 | 0.5226 | 0.9082   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2