---
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: vit5-base-transcript-summarizer
  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. -->

# vit5-base-transcript-summarizer

This model is a fine-tuned version of [VietAI/vit5-base](https://huggingface.co/VietAI/vit5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5995
- Rouge1: 52.1518
- Rouge2: 28.7254
- Rougel: 41.1877
- Rougelsum: 46.0726
- Gen Len: 16.5342

## 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.6432        | 1.0   | 1842 | 0.6072          | 50.2818 | 27.4589 | 39.9803 | 44.436    | 15.7775 |
| 0.5389        | 2.0   | 3684 | 0.5928          | 51.449  | 28.8498 | 41.1803 | 45.7102   | 16.2433 |
| 0.4847        | 3.0   | 5526 | 0.5941          | 51.2837 | 28.3449 | 40.5158 | 45.1193   | 16.0562 |
| 0.4398        | 4.0   | 7368 | 0.5995          | 52.1518 | 28.7254 | 41.1877 | 46.0726   | 16.5342 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2