CeLLaTe-ner-3class-bioformer16l-tapt-tokenizer-original-wwmask

Mardiyyah/CeLLaTe-ner-3class-bioformer16l-tapt-tokenizer-original-wwmask

CeLLaTe-ner-3class-bioformer16l-tapt-tokenizer-original-wwmask is a token classification model from Mardiyyah. 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: bert
Access: Public
Created: Jul 25, 2026
Updated: Jul 25, 2026
SHA: 6eda0f8f

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Base models

Mardiyyah/CeLLaTe-tapt-bioformer16l-tokenizer-original-wwmask

Model card

From the Hugging Face model README

CeLLaTe-ner-3class-bioformer16l-tapt-tokenizer-original-wwmask

This model is a fine-tuned version of Mardiyyah/CeLLaTe-tapt-bioformer16l-tokenizer-original-wwmask on the OTAR3088/CeLLaTe-ner-3class-iob_final dataset. It achieves the following results on the evaluation set:

Loss: 0.1025
Precision: 0.7686
Recall: 0.7562
Micro F1: 0.7624
Weighted F1: 0.7623
Macro F1: 0.7515
Accuracy: 0.9804

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: 3407
gradient_accumulation_steps: 2
total_train_batch_size: 32
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
lr_scheduler_warmup_ratio: 0.01
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	Micro F1	Weighted F1	Macro F1	Accuracy
0.418	1.0	263	0.1076	0.3909	0.4415	0.4146	0.4128	0.3775	0.9628
0.0808	2.0	526	0.0762	0.7292	0.6597	0.6927	0.6919	0.6815	0.9775
0.049	3.0	789	0.0718	0.7163	0.6959	0.7060	0.7064	0.7005	0.9780
0.036	4.0	1052	0.0821	0.7710	0.6774	0.7212	0.7180	0.7053	0.9784
0.0275	5.0	1315	0.0797	0.7620	0.7176	0.7391	0.7387	0.7305	0.9796
0.0217	6.0	1578	0.0882	0.7241	0.7089	0.7164	0.7172	0.7120	0.9779
0.0185	7.0	1841	0.0876	0.7423	0.7271	0.7346	0.7350	0.7274	0.9787
0.0149	8.0	2104	0.0989	0.7569	0.7089	0.7322	0.7316	0.7232	0.9789
0.0126	9.0	2367	0.0917	0.7483	0.7519	0.7501	0.7501	0.7396	0.9794
0.0115	10.0	2630	0.0952	0.7316	0.7184	0.7250	0.7255	0.7182	0.9787
0.0098	11.0	2893	0.0999	0.7415	0.7298	0.7356	0.7354	0.7270	0.9789
0.0086	12.0	3156	0.0973	0.7631	0.7550	0.7591	0.7590	0.7500	0.9804
0.0079	13.0	3419	0.1056	0.7129	0.7294	0.7210	0.7217	0.7138	0.9777
0.0074	14.0	3682	0.1067	0.7753	0.7432	0.7589	0.7588	0.7483	0.9802
0.0065	15.0	3945	0.1025	0.7686	0.7562	0.7624	0.7623	0.7515	0.9804
0.0059	16.0	4208	0.1073	0.7573	0.7511	0.7542	0.7543	0.7470	0.9799
0.0054	17.0	4471	0.1105	0.7607	0.7436	0.7520	0.7523	0.7438	0.9801
0.0052	18.0	4734	0.1106	0.7472	0.7487	0.7480	0.7486	0.7402	0.9796
0.0049	19.0	4997	0.1130	0.7488	0.7456	0.7472	0.7473	0.7392	0.9796
0.0047	20.0	5260	0.1123	0.7542	0.7519	0.7531	0.7531	0.7448	0.9799

Framework versions

Transformers 4.48.2
Pytorch 2.4.1+cu121
Datasets 3.0.2
Tokenizers 0.21.0

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Languages: en
Created: Jul 25, 2026
Updated: Jul 25, 2026