---
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: mymodel_base_10k_sample_2e5_v2
  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_v2

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: 1.8988
- Rouge1: 0.5793
- Rouge2: 0.2711
- Rougel: 0.3756
- Rougelsum: 0.3756
- Gen Len: 39.782

## 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 1.9788        | 1.0   | 2000  | 1.8380          | 0.5644 | 0.2515 | 0.3604 | 0.3603    | 42.489  |
| 1.7232        | 2.0   | 4000  | 1.8040          | 0.5665 | 0.2592 | 0.3675 | 0.3674    | 39.2215 |
| 1.5036        | 3.0   | 6000  | 1.8337          | 0.5682 | 0.26   | 0.3674 | 0.3674    | 38.9015 |
| 1.3468        | 4.0   | 8000  | 1.8675          | 0.5728 | 0.2664 | 0.3706 | 0.3707    | 38.9095 |
| 1.2546        | 5.0   | 10000 | 1.8988          | 0.5793 | 0.2711 | 0.3756 | 0.3756    | 39.782  |


### Framework versions

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