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---
license: mit
base_model: VietAI/vit5-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: sentiment_oversampling_25_12
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. -->
# sentiment_oversampling_25_12
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: 0.1955
- F1: 0.6240
- Accuracy: 0.7911
## 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: 1e-05
- train_batch_size: 80
- eval_batch_size: 80
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
| 1.2607 | 0.37 | 200 | 0.2220 | 0.5931 | 0.7885 |
| 0.2748 | 0.75 | 400 | 0.2099 | 0.6012 | 0.7954 |
| 0.2591 | 1.12 | 600 | 0.1922 | 0.6114 | 0.8117 |
| 0.2519 | 1.5 | 800 | 0.1993 | 0.6203 | 0.7975 |
| 0.2442 | 1.87 | 1000 | 0.2153 | 0.6092 | 0.7555 |
| 0.2408 | 2.24 | 1200 | 0.1915 | 0.6182 | 0.7992 |
| 0.2309 | 2.62 | 1400 | 0.2064 | 0.6109 | 0.7703 |
| 0.2322 | 2.99 | 1600 | 0.1972 | 0.6169 | 0.7881 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0