---
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-samsum-01
  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: 39.8989
---

<!-- 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-samsum-01

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: 1.8784
- Rouge1: 39.8989
- Rouge2: 18.4549
- Rougel: 34.2186
- Rougelsum: 37.3438

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 4.1361        | 1.0   | 1842  | 2.1341          | 35.9845 | 15.146  | 30.819  | 33.4492   |
| 2.5514        | 2.0   | 3684  | 2.0119          | 37.8344 | 16.359  | 32.2541 | 35.4021   |
| 2.3851        | 3.0   | 5526  | 1.9674          | 38.8153 | 17.1048 | 33.2513 | 36.2178   |
| 2.2878        | 4.0   | 7368  | 1.9211          | 39.0649 | 17.5803 | 33.5863 | 36.4784   |
| 2.2202        | 5.0   | 9210  | 1.9016          | 39.5536 | 18.199  | 34.1462 | 37.1727   |
| 2.181         | 6.0   | 11052 | 1.8829          | 39.8724 | 18.1549 | 34.1958 | 37.2659   |
| 2.153         | 7.0   | 12894 | 1.8821          | 39.871  | 18.4563 | 34.2479 | 37.4525   |
| 2.138         | 8.0   | 14736 | 1.8784          | 39.8989 | 18.4549 | 34.2186 | 37.3438   |


### Framework versions

- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3