learning_rate: 2e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Erson B	Erson I	Oc B	Oc I	Roduct B	Roduct I	Vent B	Vent I	Overall Precision	Overall Recall	Overall F1	Overall Accuracy
No log	1.0	300	0.0442	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 296}	{'precision': 0.9473684210526315, 'recall': 0.972972972972973, 'f1': 0.9599999999999999, 'number': 296}	{'precision': 0.9153225806451613, 'recall': 0.899009900990099, 'f1': 0.9070929070929071, 'number': 505}	{'precision': 0.9560669456066946, 'recall': 0.904950495049505, 'f1': 0.9298067141403866, 'number': 505}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 57}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 57}	{'precision': 0.9841269841269841, 'recall': 1.0, 'f1': 0.9919999999999999, 'number': 62}	{'precision': 1.0, 'recall': 0.987012987012987, 'f1': 0.9934640522875817, 'number': 77}	0.9562	0.9418	0.9489	0.9862
0.2261	2.0	600	0.0001	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 296}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 296}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 505}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 505}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 57}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 57}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 62}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 77}	1.0	1.0	1.0	1.0
0.2261	3.0	900	0.0000	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 296}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 296}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 505}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 505}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 57}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 57}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 62}	{'precision': 1.0, 'recall': 1.0, 'f1': 1.0, 'number': 77}	1.0	1.0	1.0	1.0

Framework versions

Transformers 4.46.3
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.20.3

huy1211/roberta-finetuned-ner-en

roberta-finetuned-ner-en

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

huy1211/
roberta-finetuned-ner-en