rubert-base-morph-tagging – AI Model by igorktech | AlphaNeural AI | AlphaNeural AI

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igorktech/
rubert-base-morph-tagging

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token-classification

generated_from_trainer

DeepPavlov/rubert-base-cased

autotrain_compatible

endpoints_compatible

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rubert-base-cased-token

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

Loss: 0.2595
Precision: 0.9304
Recall: 0.9334
F1: 0.9319
Accuracy: 0.9424

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

Tokens classification from OpenCorpora: opencorpora.org

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: 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	69	0.6926	0.7731	0.7674	0.7702	0.8200
No log	2.0	138	0.3744	0.8665	0.8807	0.8735	0.9003
No log	3.0	207	0.2891	0.9004	0.9071	0.9037	0.9231
No log	4.0	276	0.2566	0.9123	0.9217	0.9170	0.9327
No log	5.0	345	0.2587	0.9211	0.9255	0.9233	0.9366
No log	6.0	414	0.2472	0.9264	0.9289	0.9276	0.9401
No log	7.0	483	0.2589	0.9267	0.9313	0.9290	0.9406
0.3825	8.0	552	0.2559	0.9286	0.9334	0.9310	0.9416
0.3825	9.0	621	0.2578	0.9304	0.9339	0.9321	0.9425
0.3825	10.0	690	0.2595	0.9304	0.9334	0.9319	0.9424

Framework versions

Transformers 4.25.1
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2