wav2vec2-large-xlsr-korean-demo-test2

NX2411/wav2vec2-large-xlsr-korean-demo-test2

wav2vec2-large-xlsr-korean-demo-test2 is a automatic speech recognition model from NX2411. Use it when you need speech turned into text. 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: Automatic Speech Recognition
Library: transformers
License: apache-2.0
Model type: wav2vec2
Access: Public
Created: Aug 19, 2022
Updated: Aug 20, 2022
SHA: 87dc428e

Model card

From the Hugging Face model README

wav2vec2-large-xlsr-korean-demo-test2

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.0566
Wer: 0.5224

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: 0.0003
train_batch_size: 4
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 8
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
31.2541	0.3	400	5.4002	1.0
4.9419	0.59	800	5.3336	1.0
4.8926	0.89	1200	5.0531	1.0
4.7218	1.19	1600	4.5172	1.0
4.0218	1.49	2000	3.1418	0.9518
3.0654	1.78	2400	2.4376	0.9041
2.6226	2.08	2800	2.0151	0.8643
2.2944	2.38	3200	1.8025	0.8290
2.1872	2.67	3600	1.6469	0.7962
2.0747	2.97	4000	1.5165	0.7714
1.8479	3.27	4400	1.4281	0.7694
1.8288	3.57	4800	1.3791	0.7326
1.801	3.86	5200	1.3328	0.7177
1.6723	4.16	5600	1.2954	0.7192
1.5925	4.46	6000	1.3137	0.6953
1.5709	4.75	6400	1.2086	0.6973
1.5294	5.05	6800	1.1811	0.6730
1.3844	5.35	7200	1.2053	0.6769
1.3906	5.65	7600	1.1287	0.6556
1.4088	5.94	8000	1.1251	0.6466
1.2989	6.24	8400	1.1577	0.6546
1.2523	6.54	8800	1.0643	0.6377
1.2651	6.84	9200	1.0865	0.6417
1.2209	7.13	9600	1.0981	0.6272
1.1435	7.43	10000	1.1195	0.6317
1.1616	7.73	10400	1.0672	0.6327
1.1272	8.02	10800	1.0413	0.6248
1.043	8.32	11200	1.0555	0.6233
1.0523	8.62	11600	1.0372	0.6178
1.0208	8.92	12000	1.0170	0.6128
0.9895	9.21	12400	1.0354	0.5934
0.95	9.51	12800	1.1019	0.6039
0.9705	9.81	13200	1.0229	0.5855
0.9202	10.1	13600	1.0364	0.5919
0.8644	10.4	14000	1.0721	0.5984
0.8641	10.7	14400	1.0383	0.5905
0.8924	11.0	14800	0.9947	0.5760
0.7914	11.29	15200	1.0270	0.5885
0.7882	11.59	15600	1.0271	0.5741
0.8116	11.89	16000	0.9937	0.5741
0.7584	12.18	16400	0.9924	0.5626
0.7051	12.48	16800	1.0023	0.5572
0.7232	12.78	17200	1.0479	0.5512
0.7149	13.08	17600	1.0475	0.5765
0.6579	13.37	18000	1.0218	0.5552
0.6615	13.67	18400	1.0339	0.5631
0.6629	13.97	18800	1.0239	0.5621
0.6221	14.26	19200	1.0331	0.5537
0.6159	14.56	19600	1.0640	0.5532
0.6032	14.86	20000	1.0192	0.5567
0.5748	15.16	20400	1.0093	0.5507
0.5614	15.45	20800	1.0458	0.5472
0.5626	15.75	21200	1.0318	0.5398
0.5429	16.05	21600	1.0112	0.5278
0.5407	16.34	22000	1.0120	0.5278
0.511	16.64	22400	1.0335	0.5249
0.5316	16.94	22800	1.0146	0.5348
0.4949	17.24	23200	1.0287	0.5388
0.496	17.53	23600	1.0229	0.5348
0.4986	17.83	24000	1.0094	0.5313
0.4787	18.13	24400	1.0620	0.5234
0.4508	18.42	24800	1.0401	0.5323
0.4754	18.72	25200	1.0543	0.5303
0.4584	19.02	25600	1.0433	0.5194
0.4431	19.32	26000	1.0597	0.5249
0.4448	19.61	26400	1.0548	0.5229
0.4475	19.91	26800	1.0566	0.5224

Framework versions

Transformers 4.21.1
Pytorch 1.12.1+cu113
Datasets 2.4.0
Tokenizers 0.12.1

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Aug 19, 2022
Updated: Aug 20, 2022