transformers pytorch t5 text2text-generation generated_from_trainer base_model:VietAI/vit5-base-vietnews-summarization base_model:finetune:VietAI/vit5-base-vietnews-summarization license:mit autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: VietAI/vit5-base-vietnews-summarization
license: mit
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: vit5-base-vietnews-summarization-standardized-number
  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. -->

# vit5-base-vietnews-summarization-standardized-number

This model is a fine-tuned version of [VietAI/vit5-base-vietnews-summarization](https://huggingface.co/VietAI/vit5-base-vietnews-summarization) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8266
- Rouge1: 80.3861
- Rouge2: 75.4112
- Rougel: 80.0172
- Rougelsum: 79.9721
- Gen Len: 7.7504

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 297  | 0.6401          | 77.9012 | 72.733  | 77.2694 | 77.2675   | 8.9022  |
| 0.7223        | 2.0   | 594  | 0.5931          | 78.4299 | 73.3202 | 78.0444 | 78.0744   | 8.7437  |
| 0.7223        | 3.0   | 891  | 0.6182          | 79.3604 | 74.2323 | 78.907  | 78.9878   | 7.5497  |
| 0.3472        | 4.0   | 1188 | 0.6134          | 79.7284 | 74.8063 | 79.3057 | 79.3545   | 8.5245  |
| 0.3472        | 5.0   | 1485 | 0.6625          | 79.7185 | 74.5798 | 79.3356 | 79.3615   | 8.2749  |
| 0.2388        | 6.0   | 1782 | 0.7068          | 79.7276 | 74.6552 | 79.2519 | 79.2253   | 8.0489  |
| 0.1551        | 7.0   | 2079 | 0.7646          | 80.3805 | 75.394  | 79.9394 | 79.8915   | 7.9983  |
| 0.1551        | 8.0   | 2376 | 0.7736          | 81.2428 | 76.358  | 80.8152 | 80.8272   | 7.6121  |
| 0.1127        | 9.0   | 2673 | 0.8175          | 80.8907 | 76.0278 | 80.3848 | 80.3953   | 7.6543  |
| 0.1127        | 10.0  | 2970 | 0.8266          | 80.3861 | 75.4112 | 80.0172 | 79.9721   | 7.7504  |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
