RuNERkestra – AI Model by damienliccia | AlphaNeural AI

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damienliccia/
RuNERkestra

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token-classification

generated_from_trainer

DeepPavlov/rubert-base-cased

autotrain_compatible

endpoints_compatible

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RuNERkestra

This model is a fine-tuned version of DeepPavlov/rubert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.1935
Accuracy: 0.9355
Precision: 0.6849
Recall: 0.6321
F1: 0.6574

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: 16
seed: 42
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
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.196	1.0	5929	0.1996	0.9330	0.6644	0.6245	0.6439
0.1634	2.0	11858	0.1935	0.9355	0.6849	0.6321	0.6574
0.1613	3.0	17787	0.2030	0.9317	0.6643	0.6548	0.6595
0.1782	4.0	23716	0.2035	0.9347	0.6802	0.6557	0.6677
0.129	5.0	29645	0.2147	0.9331	0.6728	0.6559	0.6642
0.0993	6.0	35574	0.2258	0.9326	0.6679	0.6590	0.6634

Framework versions

Transformers 4.47.1
Pytorch 2.5.1+cu121
Tokenizers 0.21.0