metadata

license: apache-2.0
language:
  - ru
tags:
  - generated_from_trainer
  - robust-speech-event
datasets:
  - common_voice
model-index:
  - name: wav2vec2-xls-r-300m-Russian-small
    results:
      - task:
          name: Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice ru
          type: common_voice
          args: ru
        metrics:
          - name: Test WER
            type: wer
            value: 48.38

wav2vec2-xls-r-300m-Russian-small

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: 0.3514
Wer: 0.4838

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: 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: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.512	1.32	400	3.2207	1.0
3.1562	2.65	800	3.0166	1.0
1.5211	3.97	1200	0.7134	0.8275
0.6724	5.3	1600	0.4713	0.6402
0.4693	6.62	2000	0.3904	0.5668
0.3693	7.95	2400	0.3609	0.5121
0.3004	9.27	2800	0.3514	0.4838

Framework versions

Transformers 4.11.3
Pytorch 1.10.0+cu111
Datasets 1.14.0
Tokenizers 0.10.3