---
base_model: sanikaska/rut5_gazeta_title_generation
tags:
- generated_from_trainer
datasets:
- gazeta
metrics:
- rouge
model-index:
- name: rut5_gazeta_title_generation
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: gazeta
      type: gazeta
      config: default
      split: test
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.0594
---

<!-- 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. -->

# rut5_gazeta_title_generation

This model is a fine-tuned version of [sanikaska/rut5_gazeta_title_generation](https://huggingface.co/sanikaska/rut5_gazeta_title_generation) on the gazeta dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5882
- Rouge1: 0.0594
- Rouge2: 0.0105
- Rougel: 0.0592
- Rougelsum: 0.0592
- Gen Len: 9.6443

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.756         | 1.0   | 2500  | 2.4833          | 0.0516 | 0.0087 | 0.0514 | 0.0513    | 10.4538 |
| 2.4648        | 2.0   | 5000  | 2.4972          | 0.0583 | 0.0108 | 0.0582 | 0.0581    | 9.9832  |
| 2.306         | 3.0   | 7500  | 2.5375          | 0.0594 | 0.0104 | 0.0592 | 0.0592    | 9.4259  |
| 2.1811        | 4.0   | 10000 | 2.5882          | 0.0594 | 0.0105 | 0.0592 | 0.0592    | 9.6443  |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1