This model is a fine-tuned version of EleutherAI/gpt-neo-1.3B on the Ben10x/MedMentions-MTI881-NER dataset. It achieves the following results on the evaluation set:

Loss: 0.5111
Precision: 0.4453
Recall: 0.5247
F1: 0.4818
Accuracy: 0.8454

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: 4
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.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: 5.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.5307	1.0	5850	0.5369	0.4129	0.4711	0.4401	0.8341
0.3585	2.0	11700	0.5111	0.4453	0.5247	0.4818	0.8454
0.1758	3.0	17550	0.6349	0.4718	0.4900	0.4807	0.8497
0.0751	4.0	23400	0.9264	0.4628	0.5208	0.4901	0.8497
0.0387	5.0	29250	1.0903	0.4758	0.5181	0.4960	0.8518

Framework versions

Transformers 4.50.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

Ben10x/gpt-medmentions

gpt-medmentions

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Ben10x/
gpt-medmentions