Wolverine001/bert_finetuned_senti

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

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✅ 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

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You can download the model from Hugging Face.