---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- eur-lex-sum
metrics:
- rouge
model-index:
- name: my_legal_summarization_model
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: eur-lex-sum
      type: eur-lex-sum
      config: english
      split: test
      args: english
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.2166
---

<!-- 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. -->

# my_legal_summarization_model

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: 2.1064
- Rouge1: 0.2166
- Rouge2: 0.1493
- Rougel: 0.1992
- Rougelsum: 0.1991
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 71   | 2.3019          | 0.2114 | 0.1485 | 0.1934 | 0.1937    | 19.0    |
| No log        | 2.0   | 142  | 2.1766          | 0.2156 | 0.1508 | 0.1987 | 0.1988    | 19.0    |
| No log        | 3.0   | 213  | 2.1215          | 0.2161 | 0.1499 | 0.1988 | 0.1987    | 19.0    |
| No log        | 4.0   | 284  | 2.1064          | 0.2166 | 0.1493 | 0.1992 | 0.1991    | 19.0    |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0