biomed_roberta_all_deep – AI Model by jialinselenasong | AlphaNeural AI

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jialinselenasong/
biomed_roberta_all_deep

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token-classification

generated_from_trainer

allenai/biomed_roberta_base

autotrain_compatible

endpoints_compatible

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biomed_roberta_all_deep

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

Loss: 0.7519
Precision: 0.6732
Recall: 0.7142
F1: 0.6931
Accuracy: 0.8255

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	363	0.5600	0.6059	0.6773	0.6396	0.8131
0.7102	2.0	726	0.5290	0.6310	0.7172	0.6713	0.8248
0.4147	3.0	1089	0.5253	0.6620	0.7075	0.6840	0.8289
0.4147	4.0	1452	0.5572	0.6664	0.7062	0.6857	0.8263
0.3081	5.0	1815	0.5942	0.6615	0.7127	0.6862	0.8244
0.231	6.0	2178	0.6393	0.6745	0.7064	0.6901	0.8268
0.1864	7.0	2541	0.6771	0.6769	0.7050	0.6907	0.8250
0.1864	8.0	2904	0.7091	0.6708	0.7120	0.6908	0.8263
0.1523	9.0	3267	0.7463	0.6702	0.7159	0.6923	0.8255
0.1336	10.0	3630	0.7519	0.6732	0.7142	0.6931	0.8255

Framework versions

Transformers 4.40.1
Pytorch 2.2.1+cu121
Datasets 2.19.1
Tokenizers 0.19.1