Label 0: World

Label 1: Sports

Label 2: Business


Label 3: Sci/Tech

Epoch	Training Loss	Validation Loss
0	No log	0.199586

Fine tuned using `bert-base-uncased` model and `ag_news` dataset
{"datasets": ["ag_news"], "widget": [{"text": "After a Rocky Year, Zuckerberg Lays Out Meta\u2019s Road Map to Employees.", "example_title": "Zuckerberg Meta's road map"}, {"text": "A First Try of Apple\u2019s $3,500 Vision Pro Headset", "example_title": "Vision pro"}]}
transformers pytorch bert text-classification dataset:ag_news autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #dataset-ag_news #autotrain_compatible #endpoints_compatible #region-us 

Label 0: World

Label 1: Sports

Label 2: Business


Label 3: Sci/Tech

Epoch	Training Loss	Validation Loss
0	No log	0.199586

Fine tuned using 'bert-base-uncased' model and 'ag_news' dataset
TAGS
#transformers #pytorch #bert #text-classification #dataset-ag_news #autotrain_compatible #endpoints_compatible #region-us 
