---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Sentiment_Analysis_in_Social_Media_SonatafyAI_BERT_v1
  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_in_Social_Media_SonatafyAI_BERT_v1

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0893
- Accuracy: 0.8495

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5082        | 1.0   | 687  | 0.4134          | 0.8481   |
| 0.3337        | 2.0   | 1374 | 0.4205          | 0.8499   |
| 0.1865        | 3.0   | 2061 | 0.5330          | 0.8477   |
| 0.1099        | 4.0   | 2748 | 0.8024          | 0.8299   |
| 0.1007        | 5.0   | 3435 | 0.7997          | 0.8455   |
| 0.0393        | 6.0   | 4122 | 0.8675          | 0.8419   |
| 0.0368        | 7.0   | 4809 | 0.9558          | 0.8455   |
| 0.0308        | 8.0   | 5496 | 1.0125          | 0.8401   |
| 0.0157        | 9.0   | 6183 | 1.0818          | 0.8423   |
| 0.0156        | 10.0  | 6870 | 1.0893          | 0.8495   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1