Rodrigo1771/bioBIT-drugtemist-it-fasttext-85-ner

output

This model is a fine-tuned version of IVN-RIN/bioBIT on the Rodrigo1771/drugtemist-it-fasttext-85-ner dataset. It achieves the following results on the evaluation set:

• Loss: 0.0080
• Precision: 0.9212
• Recall: 0.9274
• F1: 0.9243
• Accuracy: 0.9986

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
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 10.0

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	0.9989	451	0.0051	0.9326	0.8703	0.9004	0.9984
0.0116	2.0	903	0.0049	0.9066	0.9206	0.9135	0.9985
0.0034	2.9989	1354	0.0056	0.8990	0.9216	0.9101	0.9984
0.0018	4.0	1806	0.0066	0.9094	0.9235	0.9164	0.9985
0.0011	4.9989	2257	0.0056	0.9082	0.9293	0.9187	0.9986
0.0007	6.0	2709	0.0068	0.9145	0.9109	0.9127	0.9985
0.0005	6.9989	3160	0.0076	0.8880	0.9284	0.9077	0.9984
0.0003	8.0	3612	0.0080	0.9094	0.9235	0.9164	0.9986
0.0002	8.9989	4063	0.0078	0.9162	0.9206	0.9184	0.9986
0.0001	9.9889	4510	0.0080	0.9212	0.9274	0.9243	0.9986

Framework versions

• Transformers 4.44.2
• Pytorch 2.4.0+cu121
• Datasets 2.21.0
• Tokenizers 0.19.1