deeptij2007/distilbert_bc2gm_corpus

my_awesome_wnut_model

This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0855
• Precision: 0.6957
• Recall: 0.7594
• F1: 0.7261
• Accuracy: 0.9687

Model description

NER model trained on spyysalo/bc2gm_corpus

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: 2e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1964	1.0	782	0.0925	0.6539	0.7442	0.6961	0.9639
0.0737	2.0	1564	0.0855	0.6957	0.7594	0.7261	0.9687

Framework versions

• Transformers 4.55.4
• Pytorch 2.8.0+cu128
• Datasets 4.0.0
• Tokenizers 0.21.4