rubert-base-cased-sentence-finetuned-sent_in_news_sents

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: 1.9506
• Accuracy: 0.7224
• F1: 0.5137

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: 14
• eval_batch_size: 14
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
No log	1.0	81	1.0045	0.6690	0.1388
No log	2.0	162	0.9574	0.6228	0.2980
No log	3.0	243	1.0259	0.6477	0.3208
No log	4.0	324	1.1262	0.6619	0.4033
No log	5.0	405	1.3377	0.6299	0.3909
No log	6.0	486	1.5716	0.6868	0.3624
0.6085	7.0	567	1.6286	0.6762	0.4130
0.6085	8.0	648	1.6450	0.6940	0.4775
0.6085	9.0	729	1.7108	0.7224	0.4920
0.6085	10.0	810	1.8792	0.7046	0.5028
0.6085	11.0	891	1.8670	0.7153	0.4992
0.6085	12.0	972	1.8856	0.7153	0.4934
0.0922	13.0	1053	1.9506	0.7224	0.5137
0.0922	14.0	1134	2.0363	0.7189	0.4761
0.0922	15.0	1215	2.0601	0.7224	0.5053
0.0922	16.0	1296	2.0813	0.7153	0.5038
0.0922	17.0	1377	2.0960	0.7189	0.5065
0.0922	18.0	1458	2.1060	0.7224	0.5098
0.0101	19.0	1539	2.1153	0.7260	0.5086
0.0101	20.0	1620	2.1187	0.7260	0.5086

Framework versions

• Transformers 4.10.3
• Pytorch 1.9.0+cu102
• Datasets 1.12.1
• Tokenizers 0.10.3