wav2vec2-large-xls-r-300m-nl

RuudVelo/wav2vec2-large-xls-r-300m-nl

wav2vec2-large-xls-r-300m-nl is a automatic speech recognition model from RuudVelo. 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: Mar 2, 2022
Updated: Mar 23, 2022
SHA: e81607e9

Datasets

common_voice

Model card

From the Hugging Face model README

wav2vec2-large-xls-r-300m-nl

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the test set:

Loss: 0.3923
Wer: 0.1748

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: 7.5e-05
train_batch_size: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 50
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.5787	0.89	400	0.6354	0.5643
0.3036	1.78	800	0.3690	0.3552
0.188	2.67	1200	0.3239	0.2958
0.1434	3.56	1600	0.3093	0.2515
0.1245	4.44	2000	0.3024	0.2433
0.1095	5.33	2400	0.3249	0.2643
0.0979	6.22	2800	0.3191	0.2281
0.0915	7.11	3200	0.3152	0.2216
0.0829	8.0	3600	0.3419	0.2218
0.0777	8.89	4000	0.3432	0.2132
0.073	9.78	4400	0.3223	0.2131
0.0688	10.67	4800	0.3094	0.2152
0.0647	11.56	5200	0.3411	0.2152
0.0639	12.44	5600	0.3762	0.2135
0.0599	13.33	6000	0.3790	0.2137
0.0572	14.22	6400	0.3693	0.2118
0.0563	15.11	6800	0.3495	0.2139
0.0521	16.0	7200	0.3800	0.2023
0.0508	16.89	7600	0.3678	0.2033
0.0513	17.78	8000	0.3845	0.1987
0.0476	18.67	8400	0.3511	0.2037
0.045	19.56	8800	0.3794	0.1994
0.044	20.44	9200	0.3525	0.2050
0.043	21.33	9600	0.4082	0.2007
0.0409	22.22	10000	0.3866	0.2004
0.0393	23.11	10400	0.3899	0.2008
0.0382	24.0	10800	0.3626	0.1951
0.039	24.89	11200	0.3936	0.1953
0.0361	25.78	11600	0.4262	0.1928
0.0362	26.67	12000	0.3796	0.1934
0.033	27.56	12400	0.3616	0.1934
0.0321	28.44	12800	0.3742	0.1933
0.0325	29.33	13200	0.3582	0.1869
0.0309	30.22	13600	0.3717	0.1874
0.029	31.11	14000	0.3814	0.1894
0.0296	32.0	14400	0.3698	0.1877
0.0281	32.89	14800	0.3976	0.1899
0.0275	33.78	15200	0.3854	0.1858
0.0264	34.67	15600	0.4021	0.1889
0.0261	35.56	16000	0.3850	0.1830
0.0242	36.44	16400	0.4091	0.1878
0.0245	37.33	16800	0.4012	0.1846
0.0243	38.22	17200	0.3996	0.1833
0.0223	39.11	17600	0.3962	0.1815
0.0223	40.0	18000	0.3898	0.1832
0.0219	40.89	18400	0.4019	0.1822
0.0211	41.78	18800	0.4035	0.1809
0.021	42.67	19200	0.3915	0.1826
0.0208	43.56	19600	0.3934	0.1784
0.0188	44.44	20000	0.3912	0.1787
0.0195	45.33	20400	0.3989	0.1766
0.0186	46.22	20800	0.3887	0.1773
0.0188	47.11	21200	0.3982	0.1758
0.0175	48.0	21600	0.3933	0.1755
0.0172	48.89	22000	0.3921	0.1749
0.0187	49.78	22400	0.3923	0.1748

Framework versions

Transformers 4.16.0.dev0
Pytorch 1.10.1+cu102
Datasets 1.17.1.dev0
Tokenizers 0.11.0

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Languages: nl
Created: Mar 2, 2022
Updated: Mar 23, 2022