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willcai/
wav2vec2_common_voice_accents_4

Name: wav2vec2_common_voice_accents_4
Availability: InStock

transformers

pytorch

wav2vec2

automatic-speech-recognition

generated_from_trainer

common_voice

apache-2.0

endpoints_compatible

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wav2vec2_common_voice_accents_4

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 evaluation set:

Loss: 0.0047

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: 48
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
total_train_batch_size: 384
total_eval_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: 30
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
4.615	1.28	400	0.8202
0.3778	2.56	800	0.1587
0.2229	3.85	1200	0.1027
0.1799	5.13	1600	0.0879
0.1617	6.41	2000	0.0772
0.1474	7.69	2400	0.0625
0.134	8.97	2800	0.0498
0.1213	10.26	3200	0.0429
0.1186	11.54	3600	0.0434
0.1118	12.82	4000	0.0312
0.1026	14.1	4400	0.0365
0.0951	15.38	4800	0.0321
0.0902	16.67	5200	0.0262
0.0843	17.95	5600	0.0208
0.0744	19.23	6000	0.0140
0.0718	20.51	6400	0.0204
0.0694	21.79	6800	0.0133
0.0636	23.08	7200	0.0104
0.0609	24.36	7600	0.0084
0.0559	25.64	8000	0.0050
0.0527	26.92	8400	0.0089
0.0495	28.21	8800	0.0058
0.0471	29.49	9200	0.0047

Framework versions

Transformers 4.17.0
Pytorch 1.10.2+cu102
Datasets 1.18.4
Tokenizers 0.11.6

willcai/wav2vec2_common_voice_accents_4

wav2vec2_common_voice_accents_4

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

willcai/
wav2vec2_common_voice_accents_4