phrasebank-sentiment-analysis – AI Model by mbrewerdavis | AlphaNeural AI

You can deploy this model and start earning money today!

mbrewerdavis/
phrasebank-sentiment-analysis

like

0

text-classification

generated_from_trainer

financial_phrasebank

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

Views

No views yet

phrasebank-sentiment-analysis

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

Loss: 0.9618
F1: 0.8428
Accuracy: 0.8549

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: 32
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Accuracy
0.0872	0.94	100	0.6726	0.8262	0.8549
0.0621	1.89	200	0.7939	0.8362	0.8556
0.0567	2.83	300	0.7211	0.8462	0.8645
0.0395	3.77	400	0.7824	0.8350	0.8556
0.0326	4.72	500	0.8522	0.8448	0.8618
0.0228	5.66	600	0.9315	0.8342	0.8466
0.0192	6.6	700	0.9355	0.8302	0.8487
0.0107	7.55	800	0.9090	0.8475	0.8611
0.0058	8.49	900	0.9500	0.8455	0.8583
0.0031	9.43	1000	0.9618	0.8428	0.8549

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1