my_awesome_wnut_model

ZONGHAOLI/my_awesome_wnut_model

my_awesome_wnut_model is a token classification model from ZONGHAOLI. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Token Classification
Library: transformers
License: apache-2.0
Model type: distilbert
Access: Public
Created: Sep 30, 2025
Updated: Oct 1, 2025
SHA: 2bd946fa

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Base models

distilbert/distilbert-base-cased

Model card

From the Hugging Face model README

my_awesome_wnut_model

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

Loss: 0.4684
Precision: 0.4865
Recall: 0.3494
F1: 0.4067
Accuracy: 0.9440

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: 2e-05
train_batch_size: 16
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	213	0.2863	0.5189	0.3179	0.3943	0.9427
No log	2.0	426	0.3160	0.4378	0.3133	0.3652	0.9418
0.0602	3.0	639	0.3395	0.5007	0.3160	0.3875	0.9422
0.0602	4.0	852	0.3650	0.5213	0.3624	0.4276	0.9443
0.0231	5.0	1065	0.3833	0.5	0.3466	0.4094	0.9434
0.0231	6.0	1278	0.3958	0.5056	0.3327	0.4013	0.9438
0.0231	7.0	1491	0.3766	0.4452	0.3800	0.41	0.9433
0.0098	8.0	1704	0.3944	0.4573	0.3624	0.4043	0.9434
0.0098	9.0	1917	0.4326	0.4897	0.3318	0.3956	0.9434
0.0047	10.0	2130	0.4203	0.4764	0.3457	0.4006	0.9437
0.0047	11.0	2343	0.4555	0.5243	0.3401	0.4126	0.9444
0.0031	12.0	2556	0.4200	0.4840	0.3642	0.4157	0.9441
0.0031	13.0	2769	0.4481	0.5014	0.3401	0.4053	0.9442
0.0031	14.0	2982	0.4410	0.4806	0.3550	0.4083	0.9438
0.0025	15.0	3195	0.4548	0.4862	0.3429	0.4022	0.9435
0.0025	16.0	3408	0.5038	0.5223	0.3151	0.3931	0.9432
0.0017	17.0	3621	0.4635	0.4668	0.3448	0.3966	0.9431
0.0017	18.0	3834	0.4699	0.4823	0.3401	0.3989	0.9439
0.0015	19.0	4047	0.4646	0.4815	0.3503	0.4056	0.9437
0.0015	20.0	4260	0.4684	0.4865	0.3494	0.4067	0.9440

Framework versions

Transformers 4.56.1
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.0

Task: Token Classification
Library: transformers
Type: distilbert
License: apache-2.0
Created: Sep 30, 2025
Updated: Oct 1, 2025