---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- eur-lex-sum
metrics:
- rouge
model-index:
- name: T5_small_eurlexsum
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: eur-lex-sum
      type: eur-lex-sum
      config: french
      split: test
      args: french
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.2
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# T5_small_eurlexsum

This model is a fine-tuned version of [t5-small](https://huggingface.co./t5-small) on the eur-lex-sum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1159
- Rouge1: 0.2
- Rouge2: 0.1394
- Rougel: 0.1833
- Rougelsum: 0.1829
- Gen Len: 19.0

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 71   | 1.4740          | 0.1718 | 0.0935 | 0.1476 | 0.1476    | 19.0    |
| No log        | 2.0   | 142  | 1.2138          | 0.1915 | 0.1207 | 0.1719 | 0.1719    | 19.0    |
| No log        | 3.0   | 213  | 1.1368          | 0.1953 | 0.1306 | 0.1759 | 0.1759    | 19.0    |
| No log        | 4.0   | 284  | 1.1159          | 0.2    | 0.1394 | 0.1833 | 0.1829    | 19.0    |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.0
- Tokenizers 0.13.3