hubert-large-korean-finetuned-korspeech-ser

byc3230/hubert-large-korean-finetuned-korspeech-ser

hubert-large-korean-finetuned-korspeech-ser is a audio classification model from byc3230. Use it for the audio classification task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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At a glance

Task: Audio Classification
Library: transformers
License: apache-2.0
Model type: hubert
Access: Public
Created: Aug 27, 2023
Updated: Aug 27, 2023
SHA: dba7030e

Model card

From the Hugging Face model README

hubert-large-korean-finetuned-korspeech-ser

This model is a fine-tuned version of team-lucid/hubert-large-korean on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.0010
Macro F1: 0.6297
Accuracy: 0.6321
Weighted f1: 0.6297
Micro f1: 0.6321
Weighted recall: 0.6321
Micro recall: 0.6321
Macro recall: 0.6321
Weighted precision: 0.6354
Micro precision: 0.6321
Macro precision: 0.6354

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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
lr_scheduler_warmup_steps: 100
num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Macro F1	Accuracy	Weighted f1	Micro f1	Weighted recall	Micro recall	Macro recall	Weighted precision	Micro precision	Macro precision
1.3419	0.28	100	1.2665	0.4034	0.4276	0.4034	0.4276	0.4276	0.4276	0.4276	0.4520	0.4276	0.4520
1.2356	0.57	200	1.2013	0.4506	0.4702	0.4506	0.4702	0.4702	0.4702	0.4702	0.4645	0.4702	0.4645
1.1905	0.85	300	1.2031	0.4480	0.4957	0.4480	0.4957	0.4957	0.4957	0.4957	0.5256	0.4957	0.5256
1.1335	1.13	400	1.1278	0.5083	0.5178	0.5083	0.5178	0.5178	0.5178	0.5178	0.5178	0.5178	0.5178
1.0794	1.42	500	1.0613	0.5507	0.5518	0.5507	0.5518	0.5518	0.5518	0.5518	0.5511	0.5518	0.5511
1.0535	1.7	600	1.0259	0.5517	0.5618	0.5517	0.5618	0.5618	0.5618	0.5618	0.5630	0.5618	0.5630
1.0396	1.99	700	1.0276	0.5514	0.5554	0.5514	0.5554	0.5554	0.5554	0.5554	0.5557	0.5554	0.5557
0.9841	2.27	800	1.0614	0.5440	0.5611	0.5440	0.5611	0.5611	0.5611	0.5611	0.5698	0.5611	0.5698
0.9527	2.55	900	1.0643	0.5405	0.5547	0.5405	0.5547	0.5547	0.5547	0.5547	0.5646	0.5547	0.5646
0.9616	2.84	1000	0.9971	0.5850	0.5895	0.5850	0.5895	0.5895	0.5895	0.5895	0.5924	0.5895	0.5924
0.9284	3.12	1100	1.0220	0.5626	0.5717	0.5626	0.5717	0.5717	0.5717	0.5717	0.5808	0.5717	0.5808
0.8744	3.4	1200	1.0368	0.5778	0.5831	0.5778	0.5831	0.5831	0.5831	0.5831	0.5884	0.5831	0.5884
0.8654	3.69	1300	1.0320	0.5925	0.5980	0.5925	0.5980	0.5980	0.5980	0.5980	0.6057	0.5980	0.6057
0.8716	3.97	1400	0.9965	0.5875	0.5930	0.5875	0.5930	0.5930	0.5930	0.5930	0.6001	0.5930	0.6001
0.7969	4.26	1500	0.9810	0.6102	0.6122	0.6102	0.6122	0.6122	0.6122	0.6122	0.6176	0.6122	0.6176
0.799	4.54	1600	0.9982	0.6075	0.6072	0.6075	0.6072	0.6072	0.6072	0.6072	0.6094	0.6072	0.6094
0.7785	4.82	1700	0.9812	0.6092	0.6136	0.6092	0.6136	0.6136	0.6136	0.6136	0.6136	0.6136	0.6136
0.7653	5.11	1800	0.9913	0.6124	0.6165	0.6124	0.6165	0.6165	0.6165	0.6165	0.6208	0.6165	0.6208
0.7192	5.39	1900	1.0057	0.6201	0.6207	0.6201	0.6207	0.6207	0.6207	0.6207	0.6244	0.6207	0.6244
0.7201	5.67	2000	1.0022	0.6207	0.6229	0.6207	0.6229	0.6229	0.6229	0.6229	0.6249	0.6229	0.6249
0.7351	5.96	2100	1.0010	0.6297	0.6321	0.6297	0.6321	0.6321	0.6321	0.6321	0.6354	0.6321	0.6354

Framework versions

Transformers 4.30.2
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3

Task: Audio Classification
Library: transformers
Type: hubert
License: apache-2.0
Created: Aug 27, 2023
Updated: Aug 27, 2023