transformers pytorch tensorboard mt5 text2text-generation summarization generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: mt5-small-finetuned-13feb-6
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mt5-small-finetuned-13feb-6

This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4645
- Rouge1: 18.09
- Rouge2: 5.09
- Rougel: 17.85

## 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: 5e-05
- train_batch_size: 10
- eval_batch_size: 10
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 7.2878        | 1.0   | 311  | 2.8276          | 8.04   | 2.25   | 7.88   |
| 3.6569        | 2.0   | 622  | 2.6625          | 15.73  | 4.67   | 15.52  |
| 3.3882        | 3.0   | 933  | 2.5924          | 16.9   | 5.12   | 16.63  |
| 3.2381        | 4.0   | 1244 | 2.5561          | 17.23  | 5.44   | 17.01  |
| 3.1386        | 5.0   | 1555 | 2.5301          | 16.92  | 5.16   | 16.69  |
| 3.0852        | 6.0   | 1866 | 2.5098          | 17.46  | 5.18   | 17.25  |
| 3.0244        | 7.0   | 2177 | 2.4873          | 17.48  | 5.05   | 17.23  |
| 2.9948        | 8.0   | 2488 | 2.4817          | 18.26  | 5.31   | 17.96  |
| 2.9542        | 9.0   | 2799 | 2.4892          | 17.97  | 5.5    | 17.68  |
| 2.9376        | 10.0  | 3110 | 2.4708          | 17.58  | 5.03   | 17.31  |
| 2.9197        | 11.0  | 3421 | 2.4697          | 18.05  | 5.05   | 17.75  |
| 2.9126        | 12.0  | 3732 | 2.4645          | 18.09  | 5.09   | 17.85  |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
