---
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: vit5-base_sentiment
  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_sentiment

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: 0.8273
- F1: 0.6438
- Accuracy: 0.6875

## 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
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | F1     | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:------:|:--------:|
| 0.8932        | 0.9984 | 312  | 0.7780          | 0.6134 | 0.669    |
| 0.7353        | 2.0    | 625  | 0.7549          | 0.6252 | 0.6745   |
| 0.6538        | 2.9984 | 937  | 0.7768          | 0.6320 | 0.6805   |
| 0.5827        | 4.0    | 1250 | 0.7904          | 0.6379 | 0.6865   |
| 0.5204        | 4.992  | 1560 | 0.8273          | 0.6438 | 0.6875   |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.20.0
- Tokenizers 0.19.1