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willcai/
wav2vec2_common_voice_accents_5

Name: wav2vec2_common_voice_accents_5
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_5

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: 0.0027

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
4.4163	1.34	400	0.5520
0.3305	2.68	800	0.1698
0.2138	4.03	1200	0.1104
0.1714	5.37	1600	0.0944
0.1546	6.71	2000	0.0700
0.1434	8.05	2400	0.0610
0.1272	9.4	2800	0.0493
0.1183	10.74	3200	0.0371
0.1113	12.08	3600	0.0468
0.1013	13.42	4000	0.0336
0.0923	14.77	4400	0.0282
0.0854	16.11	4800	0.0410
0.0791	17.45	5200	0.0252
0.0713	18.79	5600	0.0128
0.0662	20.13	6000	0.0252
0.0635	21.48	6400	0.0080
0.0607	22.82	6800	0.0098
0.0557	24.16	7200	0.0069
0.0511	25.5	7600	0.0057
0.0474	26.85	8000	0.0046
0.045	28.19	8400	0.0037
0.0426	29.53	8800	0.0027

Framework versions

Transformers 4.17.0
Pytorch 1.10.2+cu102
Datasets 1.18.4
Tokenizers 0.11.6

willcai/wav2vec2_common_voice_accents_5

wav2vec2_common_voice_accents_5

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

willcai/
wav2vec2_common_voice_accents_5