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---
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mymodel_base_10k_sample_2e5_batchsize32
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_base_10k_sample_2e5_batchsize32
This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8017
- Rouge1: 0.5626
- Rouge2: 0.2589
- Rougel: 0.3631
- Rougelsum: 0.3633
- Gen Len: 38.8535
## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.0869 | 1.0 | 500 | 1.8225 | 0.5506 | 0.2479 | 0.3552 | 0.3553 | 40.6745 |
| 1.8071 | 2.0 | 1000 | 1.8038 | 0.5589 | 0.2523 | 0.3585 | 0.3586 | 39.335 |
| 1.6991 | 3.0 | 1500 | 1.8017 | 0.5626 | 0.2589 | 0.3631 | 0.3633 | 38.8535 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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