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mmillet/rubert-tiny2_finetuned_emotion_experiment_augmented_anger_fear_no_emojis

sourceHugging Facemitupdated 4y agoView on Hugging Face

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rubert-tiny2finetunedemotionexperimentaugmentedangerfearnoemojis

This model is a fine-tuned version of cointegrated/rubert-tiny2 on an unknown dataset. It achieves the following results on the evaluation set:

—Loss: 0.5820
—Accuracy: 0.7881
—F1: 0.7886
—Precision: 0.7906
—Recall: 0.7881

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: 1e-05
—trainbatchsize: 64
—evalbatchsize: 64
—seed: 42
—optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
—lrschedulertype: linear
—num_epochs: 40

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
1.0996	1.0	69	1.0013	0.6879	0.6779	0.7070	0.6879
0.9524	2.0	138	0.8651	0.7265	0.7245	0.7322	0.7265
0.8345	3.0	207	0.7821	0.7422	0.7413	0.7445	0.7422
0.7573	4.0	276	0.7222	0.7484	0.7473	0.7482	0.7484
0.6923	5.0	345	0.6828	0.7568	0.7562	0.7562	0.7568
0.6412	6.0	414	0.6531	0.7568	0.7559	0.7556	0.7568
0.5982	7.0	483	0.6320	0.7610	0.7601	0.7597	0.7610
0.5593	8.0	552	0.6133	0.7651	0.7655	0.7664	0.7651
0.5183	9.0	621	0.6036	0.7714	0.7708	0.7709	0.7714
0.5042	10.0	690	0.5951	0.7756	0.7755	0.7760	0.7756
0.483	11.0	759	0.5878	0.7766	0.7768	0.7774	0.7766
0.4531	12.0	828	0.5855	0.7850	0.7841	0.7839	0.7850
0.4386	13.0	897	0.5828	0.7797	0.7790	0.7786	0.7797
0.4238	14.0	966	0.5788	0.7777	0.7780	0.7786	0.7777
0.4018	15.0	1035	0.5793	0.7839	0.7842	0.7855	0.7839
0.3998	16.0	1104	0.5801	0.7850	0.7844	0.7841	0.7850
0.3747	17.0	1173	0.5791	0.7839	0.7836	0.7833	0.7839
0.3595	18.0	1242	0.5799	0.7891	0.7891	0.7894	0.7891
0.3575	19.0	1311	0.5820	0.7881	0.7886	0.7906	0.7881

Framework versions

—Transformers 4.19.2
—Pytorch 1.11.0+cu113
—Datasets 2.2.2
—Tokenizers 0.12.1