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

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

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