--- 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 - hf-asr-leaderboard 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 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 8.0 type: mozilla-foundation/common_voice_8_0 args: kk metrics: - name: Test WER type: wer value: 41.7 - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Test Data type: speech-recognition-community-v2/eval_data args: kk metrics: - name: Test WER type: wer value: 67.09 --- # This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/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 2. 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