---
library_name: transformers
license: apache-2.0
base_model: google/mt5-small
tags:
- summarization
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: samsum
      type: samsum
      config: samsum
      split: validation
      args: samsum
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.4303256962227823
---

<!-- 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. -->

# mt5-small-finetuned

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7974
- Rouge1: 0.4303
- Rouge2: 0.2038
- Rougel: 0.3736
- Rougelsum: 0.3734

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.1585        | 1.0   | 1842  | 1.9205          | 0.4074 | 0.1838 | 0.3517 | 0.3518    |
| 2.1545        | 2.0   | 3684  | 1.8882          | 0.4120 | 0.1914 | 0.3592 | 0.3588    |
| 2.0888        | 3.0   | 5526  | 1.8290          | 0.4196 | 0.1939 | 0.3603 | 0.3601    |
| 2.0272        | 4.0   | 7368  | 1.8269          | 0.4215 | 0.1975 | 0.3637 | 0.3635    |
| 1.9871        | 5.0   | 9210  | 1.8224          | 0.4231 | 0.1943 | 0.3634 | 0.3633    |
| 1.9535        | 6.0   | 11052 | 1.8055          | 0.4285 | 0.2030 | 0.3715 | 0.3715    |
| 1.9322        | 7.0   | 12894 | 1.7954          | 0.4270 | 0.2018 | 0.3698 | 0.3697    |
| 1.9181        | 8.0   | 14736 | 1.7974          | 0.4303 | 0.2038 | 0.3736 | 0.3734    |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0