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: 1.9680
Wer: 0.7283

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: 16
eval_batch_size: 16
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: 180
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
8.2615	24.97	400	3.4784	1.0
3.366	49.97	800	2.3662	0.9917
1.1678	74.97	1200	1.4806	0.7709
0.5496	99.97	1600	1.7166	0.7476
0.4101	124.97	2000	1.8473	0.7510
0.3317	149.97	2400	1.9177	0.7322
0.2956	174.97	2800	1.9680	0.7283

Framework versions

Transformers 4.16.2
Pytorch 1.10.1+cu102
Datasets 1.17.1.dev0
Tokenizers 0.10.3

Evaluations Result

WER: 0.7539
CER: 0.2928

reichenbach/wav2vec2-large-xls-r-300m-pa-in

wav2vec2-large-xls-r-300m-pa-in

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Evaluations Result

reichenbach/
wav2vec2-large-xls-r-300m-pa-in