---
license: mit
base_model: ai-forever/ruElectra-medium
tags:
- generated_from_trainer
metrics:
- accuracy
- recall
- precision
- f1
model-index:
- name: training_results
  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. -->

# training_results

This model is a fine-tuned version of [ai-forever/ruElectra-medium](https://huggingface.co/ai-forever/ruElectra-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6856
- Accuracy: 0.7135
- Recall: 0.6688
- Precision: 0.7321
- F1: 0.6855

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- 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 | Accuracy | Recall | Precision | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 200  | 1.0503          | 0.6462   | 0.5404 | 0.5573    | 0.5309 |
| No log        | 2.0   | 400  | 0.9312          | 0.6842   | 0.6358 | 0.6068    | 0.5981 |
| 0.9761        | 3.0   | 600  | 0.9141          | 0.7193   | 0.6410 | 0.6629    | 0.6447 |
| 0.9761        | 4.0   | 800  | 1.1036          | 0.7193   | 0.6453 | 0.6843    | 0.6516 |
| 0.3389        | 5.0   | 1000 | 1.3396          | 0.7135   | 0.6512 | 0.7203    | 0.6576 |
| 0.3389        | 6.0   | 1200 | 1.4660          | 0.7251   | 0.6688 | 0.7587    | 0.6759 |
| 0.3389        | 7.0   | 1400 | 1.4835          | 0.7135   | 0.6656 | 0.6910    | 0.6640 |
| 0.1627        | 8.0   | 1600 | 1.8635          | 0.7135   | 0.6535 | 0.7441    | 0.6673 |
| 0.1627        | 9.0   | 1800 | 1.5689          | 0.7368   | 0.7140 | 0.7412    | 0.7192 |
| 0.0893        | 10.0  | 2000 | 1.9628          | 0.7047   | 0.6885 | 0.7050    | 0.6842 |
| 0.0893        | 11.0  | 2200 | 1.9155          | 0.7339   | 0.6814 | 0.7328    | 0.6995 |
| 0.0893        | 12.0  | 2400 | 2.0020          | 0.7398   | 0.7086 | 0.7351    | 0.7064 |
| 0.0781        | 13.0  | 2600 | 2.0432          | 0.7193   | 0.7005 | 0.7265    | 0.6876 |
| 0.0781        | 14.0  | 2800 | 1.8877          | 0.7544   | 0.7385 | 0.7634    | 0.7415 |
| 0.0435        | 15.0  | 3000 | 2.2208          | 0.7281   | 0.6876 | 0.7271    | 0.6871 |
| 0.0435        | 16.0  | 3200 | 1.9514          | 0.7485   | 0.7071 | 0.7438    | 0.7169 |
| 0.0435        | 17.0  | 3400 | 2.0358          | 0.7368   | 0.7551 | 0.7406    | 0.7402 |
| 0.0405        | 18.0  | 3600 | 2.2364          | 0.7310   | 0.6250 | 0.6655    | 0.6307 |
| 0.0405        | 19.0  | 3800 | 2.3225          | 0.7164   | 0.6779 | 0.7234    | 0.6868 |
| 0.0511        | 20.0  | 4000 | 2.1369          | 0.7310   | 0.6826 | 0.7670    | 0.7089 |
| 0.0511        | 21.0  | 4200 | 2.2229          | 0.7427   | 0.6981 | 0.7783    | 0.7145 |
| 0.0511        | 22.0  | 4400 | 2.2711          | 0.7222   | 0.6650 | 0.7214    | 0.6671 |
| 0.0382        | 23.0  | 4600 | 2.4241          | 0.7222   | 0.6556 | 0.7826    | 0.6834 |
| 0.0382        | 24.0  | 4800 | 2.0575          | 0.7368   | 0.6767 | 0.7238    | 0.6804 |
| 0.0413        | 25.0  | 5000 | 2.5485          | 0.7076   | 0.6681 | 0.6842    | 0.6682 |
| 0.0413        | 26.0  | 5200 | 2.2235          | 0.7222   | 0.6474 | 0.6889    | 0.6536 |
| 0.0413        | 27.0  | 5400 | 2.5252          | 0.7105   | 0.6835 | 0.7028    | 0.6793 |
| 0.035         | 28.0  | 5600 | 2.5843          | 0.7164   | 0.6438 | 0.7341    | 0.6654 |
| 0.035         | 29.0  | 5800 | 2.6856          | 0.7135   | 0.6688 | 0.7321    | 0.6855 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.14.5
- Tokenizers 0.14.1