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metadata
language:
  - kk
license: apache-2.0
tags:
  - automatic-speech-recognition
  - mozilla-foundation/common_voice_8_0
  - generated_from_trainer
  - kk
  - robust-speech-event
  - model_for_talk
datasets:
  - mozilla-foundation/common_voice_8_0
model-index:
  - name: wav2vec2-large-xls-r-300m-kk-with-LM
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 8
          type: mozilla-foundation/common_voice_8_0
          args: ru
        metrics:
          - name: Test WER
            type: wer
            value: 0.4355
          - name: Test CER
            type: cer
            value: 0.10469915859660263
          - name: Test WER (+LM)
            type: wer
            value: 0.417
          - name: Test CER (+LM)
            type: cer
            value: 0.10319098269566598
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Robust Speech Event - Dev Data
          type: speech-recognition-community-v2/dev_data
          args: kk
        metrics:
          - name: Test WER
            type: wer
            value: NA
          - name: Test CER
            type: cer
            value: NA

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - KK dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7149
  • Wer: 0.451

Evaluation Commands

  1. To evaluate on mozilla-foundation/common_voice_8_0 with test split

python eval.py --model_id DrishtiSharma/wav2vec2-large-xls-r-300m-kk-with-LM --dataset mozilla-foundation/common_voice_8_0 --config kk --split test --log_outputs

  1. To evaluate on speech-recognition-community-v2/dev_data

Kazakh language isn't available in speech-recognition-community-v2/dev_data

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 0.000222
  • 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: 1000
  • num_epochs: 150.0
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
9.6799 9.09 200 3.6119 1.0
3.1332 18.18 400 2.5352 1.005
1.0465 27.27 600 0.6169 0.682
0.3452 36.36 800 0.6572 0.607
0.2575 45.44 1000 0.6527 0.578
0.2088 54.53 1200 0.6828 0.551
0.158 63.62 1400 0.7074 0.5575
0.1309 72.71 1600 0.6523 0.5595
0.1074 81.8 1800 0.7262 0.5415
0.087 90.89 2000 0.7199 0.521
0.0711 99.98 2200 0.7113 0.523
0.0601 109.09 2400 0.6863 0.496
0.0451 118.18 2600 0.6998 0.483
0.0378 127.27 2800 0.6971 0.4615
0.0319 136.36 3000 0.7119 0.4475
0.0305 145.44 3200 0.7181 0.459

Framework versions

  • Transformers 4.17.0.dev0
  • Pytorch 1.10.2+cu102
  • Datasets 1.18.2.dev0
  • Tokenizers 0.11.0

Evaluation Command

!python eval.py
--model_id DrishtiSharma/wav2vec2-xls-r-300m-kk-n2
--dataset mozilla-foundation/common_voice_8_0 --config kk --split test --log_outputs