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---
license: mit
base_model: VietAI/vit5-large-vietnews-summarization
tags:
- generated_from_trainer
metrics:
- rouge
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
should probably proofread and complete it, then remove this comment. -->
# 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
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