This model is a fine-tuned version of michiyasunaga/BioLinkBERT-base on the Rodrigo1771/drugtemist-en-8-ner dataset. It achieves the following results on the evaluation set:

Loss: 0.0057
Precision: 0.9318
Recall: 0.9301
F1: 0.9310
Accuracy: 0.9987

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	1.0	493	0.0050	0.9288	0.9245	0.9267	0.9987
0.018	2.0	986	0.0057	0.9104	0.9189	0.9147	0.9984
0.0044	3.0	1479	0.0079	0.9362	0.9161	0.9260	0.9985
0.0023	4.0	1972	0.0057	0.9318	0.9301	0.9310	0.9987
0.0014	5.0	2465	0.0070	0.9201	0.9226	0.9214	0.9986
0.0008	6.0	2958	0.0082	0.9118	0.9254	0.9186	0.9985
0.0006	7.0	3451	0.0074	0.9172	0.9394	0.9282	0.9986
0.0003	8.0	3944	0.0085	0.9219	0.9245	0.9232	0.9985
0.0003	9.0	4437	0.0086	0.9149	0.9320	0.9234	0.9985
0.0002	10.0	4930	0.0089	0.9172	0.9292	0.9231	0.9985

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1

Rodrigo1771/BioLinkBERT-base-drugtemist-en-word2vec-8-ner

output

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Rodrigo1771/
BioLinkBERT-base-drugtemist-en-word2vec-8-ner