---
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: speller-t5-909
  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. -->

# speller-t5-909

This model is a fine-tuned version of [sberbank-ai/ruT5-large](https://huggingface.co/sberbank-ai/ruT5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0814
- Rouge1: 18.2203
- Rouge2: 5.9322
- Rougel: 17.7966
- Rougelsum: 18.2203
- Gen Len: 42.0424

## 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: 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: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 0.3022        | 0.1   | 1500  | 0.1563          | 18.2203 | 5.9322 | 17.7966 | 18.2203   | 43.4492 |
| 0.2274        | 0.2   | 3000  | 0.1311          | 18.2203 | 5.9322 | 17.7966 | 18.2203   | 42.3814 |
| 0.2001        | 0.31  | 4500  | 0.1128          | 18.2203 | 5.9322 | 17.7966 | 18.2203   | 41.9407 |
| 0.1757        | 0.41  | 6000  | 0.1063          | 18.2203 | 5.9322 | 17.7966 | 18.2203   | 42.2542 |
| 0.1612        | 0.51  | 7500  | 0.1002          | 17.9379 | 5.0847 | 17.5141 | 17.7966   | 42.339  |
| 0.1718        | 0.61  | 9000  | 0.0921          | 18.2203 | 5.9322 | 17.7966 | 18.2203   | 42.0508 |
| 0.1678        | 0.72  | 10500 | 0.0834          | 17.7966 | 5.0847 | 17.3729 | 17.7966   | 41.9831 |
| 0.1407        | 0.82  | 12000 | 0.0793          | 18.2203 | 5.9322 | 17.7966 | 18.2203   | 42.2119 |
| 0.1447        | 0.92  | 13500 | 0.0814          | 18.2203 | 5.9322 | 17.7966 | 18.2203   | 42.0424 |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2