MultiLabel-BankCustomerReview-bert-sentiment-analysis

This model is a fine-tuned version of google-bert/bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 1.2743
• F1 Micro: 0.7897
• F1 Macro: 0.4063
• Acc: 0.7897

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: 14
• eval_batch_size: 14
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Micro	F1 Macro	Acc
1.6427	1.0	3283	1.2743	0.7897	0.4063	0.7897

Framework versions

• Transformers 4.39.3
• Pytorch 2.3.0
• Datasets 2.19.0
• Tokenizers 0.15.2