transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:VietAI/vit5-base license:mit autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mymodel_base_60k_normal
  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_60k_normal

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: 1.7929
- Rouge1: 0.4579
- Rouge2: 0.2234
- Rougel: 0.3299
- Rougelsum: 0.3298
- Gen Len: 18.9966

## 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: 0.0002
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 2.0728        | 1.0   | 3125 | 1.9253          | 0.4466 | 0.2094 | 0.3195 | 0.3195    | 18.9946 |
| 1.7118        | 2.0   | 6250 | 1.8045          | 0.4536 | 0.2165 | 0.3247 | 0.3246    | 18.9975 |
| 1.3719        | 3.0   | 9375 | 1.7929          | 0.4579 | 0.2234 | 0.3299 | 0.3298    | 18.9966 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
