transformers pytorch tensorboard encoder-decoder text2text-generation generated_from_trainer autotrain_compatible endpoints_compatible region:us
---
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: bert2bert_law_summarization_tr
  results: []
---

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# bert2bert_law_summarization_tr

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: 0.9682
- Rouge1: 0.6221
- Rouge2: 0.5799
- Rougel: 0.6007
- Rougelsum: 0.6009
- Gen Len: 63.3077

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.6025        | 1.0   | 520  | 1.1210          | 0.611  | 0.5687 | 0.5885 | 0.5883    | 62.6154 |
| 1.0845        | 2.0   | 1040 | 1.0161          | 0.62   | 0.5789 | 0.601  | 0.6005    | 63.4038 |
| 0.9252        | 3.0   | 1560 | 0.9784          | 0.6249 | 0.583  | 0.6043 | 0.6045    | 63.2654 |
| 0.858         | 4.0   | 2080 | 0.9682          | 0.6221 | 0.5799 | 0.6007 | 0.6009    | 63.3077 |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3
