ft-bert-base-uncased-for-sentiment-classification

This model is a fine-tuned version of bert-base-uncased on the https://huggingface.co/datasets/takala/financial_phrasebank dataset. It achieves the following results on the evaluation set:

• Loss: 0.1120

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.1649	1.0	128	0.1319
0.1322	2.0	256	0.1232
0.0092	3.0	384	0.1120

Framework versions

• Transformers 4.44.0
• Pytorch 2.4.0
• Datasets 2.21.0
• Tokenizers 0.19.1