You can deploy this model and start earning money today!

Mardiyyah/
CeLLaTe-ner-2class-tapt-pubmedbert-tokenizer-adapted-spanmask

Name: CeLLaTe-ner-2class-tapt-pubmedbert-tokenizer-adapted-spanmask
Availability: InStock

Views

No views yet

CeLLaTe-ner-2class-tapt-pubmedbert-tokenizer-adapted-spanmask

This model is a fine-tuned version of Mardiyyah/CeLLaTe-tapt-pubmedbert-tokenizer-adapted-spanmask on the OTAR3088/CeLLaTe-ner-2class-iob_final dataset. It achieves the following results on the evaluation set:

More information needed

More information needed

More information needed

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 Loss	Epoch	Step	Validation Loss	Precision	Recall	Micro F1	Weighted F1	Macro F1	Accuracy
0.2522	1.0	263	0.0588	0.6756	0.6813	0.6784	0.6794	0.6963	0.9817
0.044	2.0	526	0.0560	0.7373	0.6903	0.7130	0.7136	0.7277	0.9824
0.0266	3.0	789	0.0596	0.7102	0.7162	0.7132	0.7144	0.7353	0.9825
0.0196	4.0	1052	0.0616	0.7427	0.7378	0.7403	0.7408	0.7530	0.9837
0.0144	5.0	1315	0.0740	0.7917	0.6969	0.7413	0.7413	0.7457	0.9831
0.0114	6.0	1578	0.0658	0.7691	0.7312	0.7497	0.7498	0.7558	0.9840
0.0087	7.0	1841	0.0781	0.7421	0.7372	0.7397	0.7398	0.7431	0.9832
0.0066	8.0	2104	0.0800	0.7926	0.7168	0.7528	0.7527	0.7623	0.9839
0.006	9.0	2367	0.0815	0.7570	0.7438	0.7504	0.7509	0.7636	0.9836
0.0049	10.0	2630	0.0846	0.7758	0.7426	0.7588	0.7592	0.7706	0.9839
0.0037	11.0	2893	0.0902	0.7643	0.7408	0.7524	0.7527	0.7628	0.9838
0.0037	12.0	3156	0.0904	0.7734	0.7492	0.7611	0.7616	0.7694	0.9845
0.0029	13.0	3419	0.0970	0.7756	0.7420	0.7585	0.7584	0.7658	0.9841
0.0026	14.0	3682	0.0915	0.7639	0.7529	0.7583	0.7587	0.7672	0.9846
0.0024	15.0	3945	0.0964	0.7638	0.7505	0.7571	0.7575	0.7684	0.9845