---
license: apache-2.0
base_model: IlyaGusev/rut5_base_sum_gazeta
tags:
- summarization_4
- generated_from_trainer
metrics:
- rouge
model-index:
- name: rut5_base_sum_gazeta-finetuned_week_gpt
  results: []
---

# rut5_base_sum_gazeta-finetuned_week_gpt

This model is a fine-tuned version of [IlyaGusev/rut5_base_sum_gazeta](https://huggingface.co/IlyaGusev/rut5_base_sum_gazeta) on Natet/gpt_week_yandex dataset.
This model is suitable for summarizing Hubr articles.

It achieves the following results on the evaluation set:
- Loss: 1.2643
- Rouge1: 38.9266
- Rouge2: 18.0587
- Rougel: 38.1447
- Rougelsum: 38.1337

## 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: 5.6e-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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 1.7691        | 1.0   | 1110 | 1.4005          | 37.7689 | 17.7394 | 36.8468 | 36.8842   |
| 1.4892        | 2.0   | 2220 | 1.3477          | 35.9349 | 16.8403 | 35.1786 | 35.2055   |
| 1.3579        | 3.0   | 3330 | 1.3079          | 37.7579 | 17.6421 | 36.8439 | 36.8182   |
| 1.2708        | 4.0   | 4440 | 1.2675          | 37.867  | 17.3909 | 36.9706 | 36.987    |
| 1.2006        | 5.0   | 5550 | 1.2703          | 38.8218 | 17.9772 | 38.001  | 37.9811   |
| 1.1519        | 6.0   | 6660 | 1.2703          | 38.0351 | 17.5386 | 37.209  | 37.1815   |
| 1.1132        | 7.0   | 7770 | 1.2593          | 38.4673 | 17.8343 | 37.529  | 37.5268   |
| 1.0932        | 8.0   | 8880 | 1.2643          | 38.9266 | 18.0587 | 38.1447 | 38.1337   |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3