bert-finetuned-youtube_sentiment_analysis

This model is a fine-tuned version of bert-base-uncased on the Youtube Comments dataset. It achieves the following results on the evaluation set:

• F1: 0.8264
• Accuracy: 0.8666

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: 16
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 32
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
No log	0.9989	459	0.5168	0.8007	0.8454
0.5307	2.0	919	0.4757	0.8293	0.8666
0.2785	2.9989	1378	0.5640	0.8292	0.8699
0.1447	4.0	1838	0.7789	0.8275	0.8645
0.0821	4.9946	2295	1.0400	0.8264	0.8666

Framework versions

• Transformers 4.46.3
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.20.3