transformers pytorch mt5 text2text-generation summarization generated_from_trainer base_model:thekenken/mt5-small-finetuned-summary-en-fr base_model:finetune:thekenken/mt5-small-finetuned-summary-en-fr license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
base_model: thekenken/mt5-small-finetuned-summary-en-fr
license: apache-2.0
metrics:
- rouge
tags:
- summarization
- generated_from_trainer
model-index:
- name: mt5-small-finetuned-summary-en-fr-finetuned-summary-en-fr
  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-summary-en-fr-finetuned-summary-en-fr

This model is a fine-tuned version of [thekenken/mt5-small-finetuned-summary-en-fr](https://huggingface.co/thekenken/mt5-small-finetuned-summary-en-fr) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2663
- Rouge1: 0.226
- Rouge2: 0.0761
- Rougel: 0.1868
- Rougelsum: 0.1867
- Gen Len: 18.9787

## 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: 3.6e-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: 5

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:------:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.4654        | 1.0   | 74615  | 2.3755          | 0.2166 | 0.0691 | 0.1789 | 0.1789    | 18.9725 |
| 2.3603        | 2.0   | 149230 | 2.3189          | 0.2222 | 0.0728 | 0.1835 | 0.1836    | 18.9777 |
| 2.3052        | 3.0   | 223845 | 2.2922          | 0.2246 | 0.0749 | 0.1854 | 0.1854    | 18.9823 |
| 2.272         | 4.0   | 298460 | 2.2733          | 0.2252 | 0.0757 | 0.1861 | 0.1861    | 18.9801 |
| 2.2532        | 5.0   | 373075 | 2.2663          | 0.226  | 0.0761 | 0.1868 | 0.1867    | 18.9787 |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.0
- Datasets 2.14.5
- Tokenizers 0.14.1
