---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- pubmed-summarization
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-amazon-en-es
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: pubmed-summarization
      type: pubmed-summarization
      config: section
      split: validation
      args: section
    metrics:
    - name: Rouge1
      type: rouge
      value: 14.1074
---

<!-- 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-amazon-en-es

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on the pubmed-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3381
- Rouge1: 14.1074
- Rouge2: 5.3407
- Rougel: 11.9593
- Rougelsum: 12.9286

## 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: 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: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 3.0498        | 1.0   | 2500  | 2.4883          | 12.7167 | 5.1639 | 10.969  | 11.902    |
| 2.8737        | 2.0   | 5000  | 2.4022          | 13.812  | 5.1042 | 11.7056 | 12.6907   |
| 2.7603        | 3.0   | 7500  | 2.3895          | 13.6588 | 5.1146 | 11.6214 | 12.5331   |
| 2.6946        | 4.0   | 10000 | 2.3523          | 13.7167 | 5.2024 | 11.669  | 12.5419   |
| 2.6527        | 5.0   | 12500 | 2.3383          | 14.082  | 5.2787 | 11.9031 | 12.875    |
| 2.6303        | 6.0   | 15000 | 2.3381          | 14.1074 | 5.3407 | 11.9593 | 12.9286   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3