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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_30k_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_30k_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: 1.7734
- Rouge1: 0.6007
- Rouge2: 0.2982
- Rougel: 0.397
- Rougelsum: 0.3967
- Gen Len: 40.4167
## 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.7493 | 1.0 | 6750 | 1.6597 | 0.5919 | 0.2925 | 0.3926 | 0.3924 | 39.202 |
| 1.2965 | 2.0 | 13500 | 1.6761 | 0.5986 | 0.2972 | 0.3962 | 0.3961 | 40.2633 |
| 1.0039 | 3.0 | 20250 | 1.7734 | 0.6007 | 0.2982 | 0.397 | 0.3967 | 40.4167 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.7
- Tokenizers 0.14.1
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