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# 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

Sentiment analysis for user's review on Meta application

## 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

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["f1", "accuracy"], "base_model": "VietAI/vit5-base", "model-index": [{"name": "sentiment_oversampling_25_12", "results": []}]}
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