biotech-sentiment-modernbert-large

akseljoonas/biotech-sentiment-modernbert-large

biotech-sentiment-modernbert-large is a text classification model from akseljoonas. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.

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

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At a glance

Task: Text Classification
Library: transformers
License: mit
Model type: modernbert
Access: Public
Created: Mar 9, 2026
Updated: Mar 9, 2026
SHA: c928812f

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Base models

thomas-sounack/BioClinical-ModernBERT-large

Model card

From the Hugging Face model README

biotech-sentiment-modernbert-large

This model is a fine-tuned version of thomas-sounack/BioClinical-ModernBERT-large on the None dataset. It achieves the following results on the evaluation set:

Loss: 4.3531
F1 Weighted: 0.5360
F1 Macro: 0.4102
F1 Micro: 0.5577
Accuracy: 0.5577
F1 Class 0: 0.2881
F1 Class 1: 0.7143
F1 Class 2: 0.2281

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: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
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: cosine
lr_scheduler_warmup_steps: 250
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Weighted	F1 Macro	F1 Micro	Accuracy	F1 Class 0	F1 Class 1	F1 Class 2
2.1818	1.0	127	1.0826	0.3588	0.3214	0.3504	0.3504	0.3487	0.4120	0.2034
2.2104	2.0	254	1.1365	0.2625	0.2229	0.2991	0.2991	0.3404	0.3185	0.0100
2.0356	3.0	381	1.2092	0.3658	0.2829	0.3722	0.3722	0.0293	0.4832	0.3363
1.6188	4.0	508	1.1989	0.3326	0.3157	0.3198	0.3198	0.2950	0.3567	0.2952
1.1139	5.0	635	1.5419	0.5282	0.4009	0.5479	0.5479	0.2277	0.7086	0.2663
0.7829	6.0	762	2.0069	0.5263	0.4022	0.5410	0.5410	0.3171	0.7022	0.1871
0.5745	7.0	889	2.6626	0.5037	0.3840	0.5035	0.5035	0.1843	0.6733	0.2943
0.4521	8.0	1016	2.7618	0.5304	0.4041	0.5508	0.5508	0.2569	0.7094	0.2460
0.3251	9.0	1143	2.9332	0.5332	0.3932	0.5706	0.5706	0.2360	0.7317	0.2118
0.2154	10.0	1270	2.9890	0.5285	0.4127	0.5350	0.5350	0.3134	0.6927	0.2321
0.1807	11.0	1397	3.2419	0.5279	0.4132	0.5321	0.5321	0.2995	0.6906	0.2493
0.0934	12.0	1524	3.5012	0.5121	0.4031	0.5104	0.5104	0.3230	0.6667	0.2196
0.0738	13.0	1651	4.1345	0.5332	0.4017	0.5607	0.5607	0.2943	0.7197	0.1911
0.0107	14.0	1778	4.0537	0.5337	0.4117	0.5499	0.5499	0.3128	0.7066	0.2156
0.0141	15.0	1905	4.0290	0.5199	0.3972	0.5301	0.5301	0.2948	0.6939	0.2029
0.0067	16.0	2032	4.3166	0.5352	0.4112	0.5558	0.5558	0.2992	0.7109	0.2235
0.0024	17.0	2159	4.3491	0.5359	0.4101	0.5577	0.5577	0.2865	0.7143	0.2294
0.0101	18.0	2286	4.3545	0.5352	0.4096	0.5568	0.5568	0.2881	0.7133	0.2274
0.0025	19.0	2413	4.3476	0.5354	0.4095	0.5568	0.5568	0.2873	0.7139	0.2274
0.0091	20.0	2540	4.3531	0.5360	0.4102	0.5577	0.5577	0.2881	0.7143	0.2281

Framework versions

Transformers 5.3.0
Pytorch 2.10.0+cu128
Datasets 4.6.1
Tokenizers 0.22.2

Task: Text Classification
Library: transformers
Type: modernbert
License: mit
Created: Mar 9, 2026
Updated: Mar 9, 2026