Loss: 0.0524
Chemical: {'precision': 0.7696030977734754, 'recall': 0.8229813664596274, 'f1-score': 0.7953976988494248, 'support': 966}
Micro avg: {'precision': 0.7696030977734754, 'recall': 0.8229813664596274, 'f1-score': 0.7953976988494248, 'support': 966}
Macro avg: {'precision': 0.7696030977734754, 'recall': 0.8229813664596274, 'f1-score': 0.7953976988494248, 'support': 966}
Weighted avg: {'precision': 0.7696030977734754, 'recall': 0.8229813664596274, 'f1-score': 0.7953976988494248, 'support': 966}

Model description

More information needed

Intended uses & limitations

More information needed

More information needed

The following hyperparameters were used during training:

Training Loss	Epoch	Step	Validation Loss	Chemical	Micro avg	Macro avg	Weighted avg
0.1661	1.0	16198	0.0916	{'precision': 0.757026291931097, 'recall': 0.8643892339544513, 'f1-score': 0.8071532141130981, 'support': 966}	{'precision': 0.757026291931097, 'recall': 0.8643892339544513, 'f1-score': 0.8071532141130981, 'support': 966}	{'precision': 0.757026291931097, 'recall': 0.8643892339544513, 'f1-score': 0.8071532141130981, 'support': 966}	{'precision': 0.757026291931097, 'recall': 0.8643892339544513, 'f1-score': 0.8071532141130981, 'support': 966}
0.0663	2.0	32396	0.0570	{'precision': 0.7653846153846153, 'recall': 0.8240165631469979, 'f1-score': 0.7936191425722832, 'support': 966}	{'precision': 0.7653846153846153, 'recall': 0.8240165631469979, 'f1-score': 0.7936191425722832, 'support': 966}	{'precision': 0.7653846153846153, 'recall': 0.8240165631469979, 'f1-score': 0.7936191425722832, 'support': 966}	{'precision': 0.7653846153846153, 'recall': 0.8240165631469979, 'f1-score': 0.7936191425722832, 'support': 966}
0.0564	3.0	48594	0.0524	{'precision': 0.7696030977734754, 'recall': 0.8229813664596274, 'f1-score': 0.7953976988494248, 'support': 966}	{'precision': 0.7696030977734754, 'recall': 0.8229813664596274, 'f1-score': 0.7953976988494248, 'support': 966}	{'precision': 0.7696030977734754, 'recall': 0.8229813664596274, 'f1-score': 0.7953976988494248, 'support': 966}	{'precision': 0.7696030977734754, 'recall': 0.8229813664596274, 'f1-score': 0.7953976988494248, 'support': 966}