---
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: fine-tuning-vit5-mlgsum-relu
  results: []
---

<!-- 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. -->

# fine-tuning-vit5-mlgsum-relu

This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1553
- Rouge1: 50.2842
- Rouge2: 21.0293
- Rougel: 33.3278
- Rougelsum: 33.59
- Gen Len: 22.7732

## 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: 1e-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
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.2569        | 1.0   | 5972  | 2.1921          | 50.1697 | 20.3516 | 33.0218 | 33.2741   | 22.798  |
| 2.1195        | 2.0   | 11944 | 2.1568          | 49.9364 | 20.7226 | 33.2213 | 33.4414   | 22.7167 |
| 1.9927        | 3.0   | 17916 | 2.1553          | 50.2842 | 21.0293 | 33.3278 | 33.59     | 22.7732 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1