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

Loss: 0.0734
Accuracy: 0.9912
F1: 0.9911

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.3209	1.0	227	0.1929	0.9558	0.9551
0.0821	2.0	454	0.0994	0.9867	0.9867
0.04	3.0	681	0.0685	0.9867	0.9866
0.0098	4.0	908	0.0980	0.9867	0.9867
0.0003	5.0	1135	0.0734	0.9912	0.9911

Framework versions

Transformers 4.21.1
Pytorch 1.12.0+cu113
Datasets 2.4.0
Tokenizers 0.12.1

Farshid/bert-large-uncased-financial-phrasebank-allagree2

bert-large-uncased-financial-phrasebank-allagree2

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Farshid/
bert-large-uncased-financial-phrasebank-allagree2