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: 2.4749
Wer: 0.9420

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
9.8626	4.76	400	3.6151	1.0
3.5463	9.52	800	3.5778	1.0
3.4415	14.28	1200	3.4525	1.0
3.0927	19.05	1600	2.6220	0.9860
2.0573	23.8	2000	2.3974	0.9610
1.5905	28.57	2400	2.4427	0.9558
1.426	33.33	2800	2.4736	0.9475
1.3147	38.09	3200	2.4494	0.9417
1.2642	42.85	3600	2.4665	0.9450
1.2289	47.62	4000	2.4749	0.9420

Framework versions

Transformers 4.11.3
Pytorch 1.10.1+cu102
Datasets 1.17.1.dev0
Tokenizers 0.10.3

reichenbach/wav2vec2-large-xls-r-300m-hi

wav2vec2-large-xls-r-300m-hi

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

reichenbach/
wav2vec2-large-xls-r-300m-hi