---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: sentiment-analysis-whatsapp
  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-analysis-whatsapp

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co./microsoft/deberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2229
- Accuracy: {'accuracy': 0.929}
- F1 Macro: 0.9285

## 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: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 99
- gradient_accumulation_steps: 5
- total_train_batch_size: 320
- 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 | Accuracy             | F1 Macro |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|:--------:|
| No log        | 1.0   | 50   | 0.6396          | {'accuracy': 0.7845} | 0.7828   |
| No log        | 2.0   | 100  | 0.2665          | {'accuracy': 0.915}  | 0.9145   |
| No log        | 3.0   | 150  | 0.2229          | {'accuracy': 0.929}  | 0.9285   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2