tensorboard safetensors mt5 summarization generated_from_trainer dataset:gazeta base_model:google/mt5-small base_model:finetune:google/mt5-small license:apache-2.0 model-index region:us
---
base_model: google/mt5-small
datasets:
- gazeta
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: mt5-small-finetuned-gazeta-ru
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: gazeta
      type: gazeta
      config: default
      split: validation
      args: default
    metrics:
    - type: rouge
      value: 2.9422
      name: Rouge1
---

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# mt5-small-finetuned-gazeta-ru

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the gazeta dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3287
- Rouge1: 2.9422
- Rouge2: 0.25
- Rougel: 2.9053
- Rougelsum: 2.9131

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 5.5708        | 1.0   | 1690  | 3.3106          | 1.8563 | 0.1911 | 1.8332 | 1.8348    |
| 4.0219        | 2.0   | 3380  | 3.3048          | 2.2018 | 0.1649 | 2.1978 | 2.2022    |
| 3.7276        | 3.0   | 5070  | 3.3320          | 3.2293 | 0.2173 | 3.194  | 3.2039    |
| 3.5835        | 4.0   | 6760  | 3.3308          | 3.2189 | 0.2932 | 3.1825 | 3.1841    |
| 3.4944        | 5.0   | 8450  | 3.3104          | 2.8833 | 0.1964 | 2.8521 | 2.8537    |
| 3.4203        | 6.0   | 10140 | 3.3032          | 2.9914 | 0.2723 | 2.9516 | 2.9542    |
| 3.3774        | 7.0   | 11830 | 3.3232          | 2.9982 | 0.3063 | 2.965  | 2.9642    |
| 3.348         | 8.0   | 13520 | 3.3287          | 2.9422 | 0.25   | 2.9053 | 2.9131    |


### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
