| | --- |
| | language: en |
| | license: mit |
| | datasets: |
| | - twitter-sentiment |
| | metrics: |
| | - accuracy |
| | - f1 |
| | - precision |
| | - recall |
| | base_model: |
| | - google-bert/bert-base-uncased |
| | pipeline_tag: text-classification |
| | library_name: transformers |
| | --- |
| | |
| | # Fine-Tuned BERT Sentiment Model |
| |
|
| | This model was fine-tuned for sentiment classification. |
| |
|
| | - Pre-trained model used: google-bert/bert-base-uncased. |
| | - Dataset used: twitter-sentiment. |
| | - max_length = 128 |
| | - batch_size = 8 |
| | - learning_rate = 1e-4 |
| | - epochs = 3 |
| | |
| | ## **Evaluation Results** |
| | |
| | ### 📌 **Before Fine-Tuning** |
| | **Accuracy:** 0.4046 |
| | |
| | | Class | Precision | Recall | F1-Score | Support | |
| | |------------|------------|------------|------------|------------| |
| | | Negative | 0.00 | 0.00 | 0.00 | 1001 | |
| | | Neutral | 0.40 | 1.00 | 0.58 | 1430 | |
| | | Positive | 0.00 | 0.00 | 0.00 | 1103 | |
| | | **Macro Avg** | 0.13 | 0.33 | 0.19 | 3534 | |
| | | **Weighted Avg** | 0.16 | 0.40 | 0.23 | 3534 | |
| | |
| | --- |
| | |
| | ### ✅ **After Fine-Tuning** |
| | **Accuracy:** 0.6095 |
| | |
| | | Class | Precision | Recall | F1-Score | Support | |
| | |------------|------------|------------|------------|------------| |
| | | Negative | 0.82 | 0.29 | 0.42 | 1001 | |
| | | Neutral | 0.51 | 0.89 | 0.65 | 1430 | |
| | | Positive | 0.85 | 0.54 | 0.66 | 1103 | |
| | | **Macro Avg** | 0.73 | 0.57 | 0.58 | 3534 | |
| | | **Weighted Avg** | 0.70 | 0.61 | 0.59 | 3534 | |
| | |
| | --- |
| | |
| | You can download the model from [Hugging Face](https://huggingface.co/Wolverine001/bert_finetuned_senti). |
