---
license: mit
base_model: alexue4/text-normalization-ru-new
tags:
- generated_from_trainer
model-index:
- name: text-normalization-ru-new
  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. -->

# text-normalization-ru-new

This model is a fine-tuned version of [alexue4/text-normalization-ru-new](https://huggingface.co/alexue4/text-normalization-ru-new) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0003
- Mean Distance: 0
- Max Distance: 0

## 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: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Distance | Max Distance |
|:-------------:|:-----:|:----:|:---------------:|:-------------:|:------------:|
| 0.0013        | 1.0   | 69   | 0.0028          | 0             | 2            |
| 0.0006        | 2.0   | 138  | 0.0026          | 0             | 3            |
| 0.0025        | 3.0   | 207  | 0.0039          | 0             | 3            |
| 0.0004        | 4.0   | 276  | 0.0037          | 0             | 3            |
| 0.0005        | 5.0   | 345  | 0.0091          | 0             | 3            |
| 0.0009        | 6.0   | 414  | 0.0006          | 0             | 0            |
| 0.0016        | 7.0   | 483  | 0.0003          | 0             | 0            |
| 0.0012        | 8.0   | 552  | 0.0111          | 0             | 5            |
| 0.0008        | 9.0   | 621  | 0.0004          | 0             | 0            |
| 0.0018        | 10.0  | 690  | 0.0003          | 0             | 0            |
| 0.0028        | 11.0  | 759  | 0.0003          | 0             | 0            |
| 0.0008        | 12.0  | 828  | 0.0003          | 0             | 0            |
| 0.001         | 13.0  | 897  | 0.0004          | 0             | 2            |
| 0.0026        | 14.0  | 966  | 0.0005          | 0             | 2            |
| 0.0015        | 15.0  | 1035 | 0.0007          | 0             | 3            |
| 0.0009        | 16.0  | 1104 | 0.0007          | 0             | 3            |
| 0.0014        | 17.0  | 1173 | 0.0003          | 0             | 0            |
| 0.001         | 18.0  | 1242 | 0.0004          | 0             | 0            |
| 0.0007        | 19.0  | 1311 | 0.0013          | 0             | 3            |
| 0.0013        | 20.0  | 1380 | 0.0013          | 0             | 3            |
| 0.0007        | 21.0  | 1449 | 0.0003          | 0             | 0            |
| 0.0016        | 22.0  | 1518 | 0.0003          | 0             | 0            |
| 0.0013        | 23.0  | 1587 | 0.0003          | 0             | 0            |
| 0.0004        | 24.0  | 1656 | 0.0003          | 0             | 0            |
| 0.001         | 25.0  | 1725 | 0.0003          | 0             | 0            |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3