transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:VietAI/vit5-large-vietnews-summarization base_model:finetune:VietAI/vit5-large-vietnews-summarization license:mit autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: VietAI/vit5-large-vietnews-summarization
license: mit
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: mymodel_larger_vietnews_10k_2e5_3epoch_batchsize4
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# mymodel_larger_vietnews_10k_2e5_3epoch_batchsize4

This model is a fine-tuned version of [VietAI/vit5-large-vietnews-summarization](https://huggingface.co/VietAI/vit5-large-vietnews-summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9223
- Rouge1: 0.5899
- Rouge2: 0.281
- Rougel: 0.3815
- Rougelsum: 0.3817
- Gen Len: 40.2035

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.8242        | 1.0   | 2000 | 1.7603          | 0.5792 | 0.2754 | 0.3786 | 0.3787    | 39.1905 |
| 1.3026        | 2.0   | 4000 | 1.8069          | 0.5884 | 0.2827 | 0.3827 | 0.3828    | 38.768  |
| 0.9538        | 3.0   | 6000 | 1.9223          | 0.5899 | 0.281  | 0.3815 | 0.3817    | 40.2035 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
