xls-r-300m-sv-cv8

hf-test/xls-r-300m-sv-cv8

xls-r-300m-sv-cv8 is a automatic speech recognition model from hf-test. 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 24, 2022
SHA: ef742096

Datasets

mozilla-foundation/common_voice_8_0

Model card

From the Hugging Face model README

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SV-SE dataset. It achieves the following results on the evaluation set:

Without LM:

Wer: 0.2465
Cer: 0.0717

With LM:

Wer: 0.1710
Cer: 0.0569

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: 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_steps: 2000
num_epochs: 50.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.3224	1.37	500	3.2676	1.0
2.9319	2.74	1000	2.9287	1.0000
2.1173	4.11	1500	1.1478	0.8788
1.6973	5.48	2000	0.6749	0.6547
1.5865	6.85	2500	0.5500	0.5634
1.5094	8.22	3000	0.4840	0.5430
1.4644	9.59	3500	0.4844	0.4142
1.4061	10.96	4000	0.4356	0.3808
1.3584	12.33	4500	0.4192	0.3698
1.3438	13.7	5000	0.3980	0.3584
1.3332	15.07	5500	0.3896	0.3572
1.3025	16.44	6000	0.3835	0.3487
1.2979	17.81	6500	0.3781	0.3417
1.2736	19.18	7000	0.3734	0.3270
1.2415	20.55	7500	0.3637	0.3316
1.2255	21.92	8000	0.3546	0.3147
1.2193	23.29	8500	0.3524	0.3196
1.2104	24.66	9000	0.3403	0.3097
1.1965	26.03	9500	0.3508	0.3093
1.1976	27.4	10000	0.3419	0.3071
1.182	28.77	10500	0.3364	0.2963
1.158	30.14	11000	0.3338	0.2932
1.1414	31.51	11500	0.3376	0.2940
1.1402	32.88	12000	0.3370	0.2891
1.1213	34.25	12500	0.3201	0.2874
1.1207	35.62	13000	0.3261	0.2826
1.1074	36.98	13500	0.3117	0.2786
1.0818	38.36	14000	0.3194	0.2776
1.0889	39.73	14500	0.3188	0.2738
1.0672	41.1	15000	0.3196	0.2773
1.0838	42.47	15500	0.3130	0.2739
1.0553	43.83	16000	0.3165	0.2704
1.0786	45.21	16500	0.3108	0.2706
1.0546	46.57	17000	0.3102	0.2677
1.0425	47.94	17500	0.3115	0.2679
1.0398	49.31	18000	0.3131	0.2666

Framework versions

Transformers 4.16.0.dev0
Pytorch 1.10.1+cu113
Datasets 1.18.1.dev0
Tokenizers 0.10.3

Task: Automatic Speech Recognition
Library: transformers
Type: wav2vec2
License: apache-2.0
Created: Mar 2, 2022
Updated: Mar 24, 2022