sberbank-rubert-base-collection3 – AI Model by viktor-shcherb | AlphaNeural AI

You can deploy this model and start earning money today!

viktor-shcherb/
sberbank-rubert-base-collection3

like

0

token-classification

generated_from_trainer

named-entity-recognition

RCC-MSU/collection3

ai-forever/ruBert-base

endpoints_compatible

Views

No views yet

sberbank-rubert-base-collection3

This model is a fine-tuned version of sberbank-ai/ruBert-base on the collection3 dataset. It achieves the following results on the validation set:

Loss: 0.0772
Precision: 0.9380
Recall: 0.9594
F1: 0.9486
Accuracy: 0.9860

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: 5e-05
train_batch_size: 4
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 0.1
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.0899	1.0	2326	0.0760	0.9040	0.9330	0.9182	0.9787
0.0522	2.0	4652	0.0680	0.9330	0.9339	0.9335	0.9821
0.0259	3.0	6978	0.0745	0.9308	0.9512	0.9409	0.9838
0.0114	4.0	9304	0.0731	0.9372	0.9573	0.9471	0.9857
0.0027	5.0	11630	0.0772	0.9380	0.9594	0.9486	0.9860

Framework versions

Transformers 4.26.1
Pytorch 1.7.0
Datasets 2.10.1
Tokenizers 0.13.2