---
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bert2bert_law_summarization
  results: []
---

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# bert2bert_law_summarization

This model is a fine-tuned version of [mrm8488/bert2bert_shared-turkish-summarization](https://huggingface.co/mrm8488/bert2bert_shared-turkish-summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1184
- Rouge1: 0.6064
- Rouge2: 0.5608
- Rougel: 0.5828
- Rougelsum: 0.5836
- Gen Len: 63.2615

## 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: 2
- eval_batch_size: 2
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.5546        | 1.0   | 520  | 1.2699          | 0.6047 | 0.5588 | 0.5795 | 0.5799    | 62.7038 |
| 1.071         | 2.0   | 1040 | 1.1607          | 0.6075 | 0.5598 | 0.5814 | 0.5824    | 63.2269 |
| 0.9101        | 3.0   | 1560 | 1.1268          | 0.6129 | 0.569  | 0.5884 | 0.5891    | 62.9654 |
| 0.798         | 4.0   | 2080 | 1.1184          | 0.6064 | 0.5608 | 0.5828 | 0.5836    | 63.2615 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3