mobilebert-uncased-biored-finetuned – AI Model by Dagobert42 | AlphaNeural AI

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Dagobert42/
mobilebert-uncased-biored-finetuned

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token-classification

low-resource NER

token_classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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Dagobert42/mobilebert-uncased-biored-finetuned

This model is a fine-tuned version of mobilebert-uncased on the bigbio/biored dataset. It achieves the following results on the evaluation set:

Loss: 1.0264
Accuracy: 0.7163
Precision: 0.1023
Recall: 0.1429
F1: 0.1192
Weighted F1: 0.5979

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: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1	Weighted F1
No log	1.0	13	1.6911	0.7114	0.1016	0.1429	0.1188	0.5914
No log	2.0	26	1.2080	0.7114	0.1016	0.1429	0.1188	0.5914
No log	3.0	39	1.0905	0.7114	0.1016	0.1429	0.1188	0.5914
No log	4.0	52	1.0400	0.7114	0.1016	0.1429	0.1188	0.5914
No log	5.0	65	1.0439	0.7114	0.1016	0.1429	0.1188	0.5914
No log	6.0	78	1.0288	0.7114	0.1016	0.1429	0.1188	0.5914
No log	7.0	91	1.0259	0.7114	0.1016	0.1429	0.1188	0.5914
No log	8.0	104	1.0180	0.7114	0.1016	0.1429	0.1188	0.5914
No log	9.0	117	1.0229	0.7114	0.1016	0.1429	0.1188	0.5914
No log	10.0	130	1.0186	0.7114	0.1016	0.1429	0.1188	0.5914

Framework versions

Transformers 4.35.2
Pytorch 2.0.1+cu117
Datasets 2.12.0
Tokenizers 0.15.0