---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: Sentiment-Analysis-on-Twitter-BCS
  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-on-Twitter-BCS

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1303
- Accuracy: 0.9615
- Precision: 0.7730
- Recall: 0.6384
- F1: 0.6993
- Roc Auc: 0.9701

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 0.211         | 1.0   | 1798 | 0.1622          | 0.9515   | 0.6769    | 0.5893 | 0.6301 | 0.9417  |
| 0.1369        | 2.0   | 3596 | 0.1568          | 0.9568   | 0.7009    | 0.6696 | 0.6849 | 0.9646  |
| 0.1118        | 3.0   | 5394 | 0.1303          | 0.9615   | 0.7730    | 0.6384 | 0.6993 | 0.9701  |
| 0.0887        | 4.0   | 7192 | 0.1532          | 0.9631   | 0.8011    | 0.6295 | 0.7050 | 0.9708  |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.0
- Tokenizers 0.13.3