rubert-base-cased-sentence-finetuned-sent_in_ru

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

• Loss: 2.3503
• Accuracy: 0.6884
• F1: 0.6875

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: 15
• eval_batch_size: 15
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 25

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	441	0.7397	0.6630	0.6530
0.771	2.0	882	0.7143	0.6909	0.6905
0.5449	3.0	1323	0.8385	0.6897	0.6870
0.3795	4.0	1764	0.8851	0.6939	0.6914
0.3059	5.0	2205	1.0728	0.6933	0.6953
0.2673	6.0	2646	1.0673	0.7060	0.7020
0.2358	7.0	3087	1.5200	0.6830	0.6829
0.2069	8.0	3528	1.3439	0.7024	0.7016
0.2069	9.0	3969	1.3545	0.6830	0.6833
0.1724	10.0	4410	1.5591	0.6927	0.6902
0.1525	11.0	4851	1.6425	0.6818	0.6823
0.131	12.0	5292	1.8999	0.6836	0.6775
0.1253	13.0	5733	1.6959	0.6884	0.6877
0.1132	14.0	6174	1.9561	0.6776	0.6803
0.0951	15.0	6615	2.0356	0.6763	0.6754
0.1009	16.0	7056	1.7995	0.6842	0.6741
0.1009	17.0	7497	2.0638	0.6884	0.6811
0.0817	18.0	7938	2.1686	0.6884	0.6859
0.0691	19.0	8379	2.0874	0.6878	0.6889
0.0656	20.0	8820	2.1772	0.6854	0.6817
0.0652	21.0	9261	2.4018	0.6872	0.6896
0.0608	22.0	9702	2.2074	0.6770	0.6656
0.0677	23.0	10143	2.2101	0.6848	0.6793
0.0559	24.0	10584	2.2920	0.6848	0.6835
0.0524	25.0	11025	2.3503	0.6884	0.6875

Framework versions

• Transformers 4.11.2
• Pytorch 1.9.0+cu102
• Datasets 1.12.1
• Tokenizers 0.10.3