--- language: - hy-AM license: apache-2.0 tags: - automatic-speech-recognition - mozilla-foundation/common_voice_8_0 - generated_from_trainer - robust-speech-event datasets: - common_voice model-index: - name: wav2vec2-xls-r-1b-hy-cv results: - task: type: automatic-speech-recognition name: Speech Recognition dataset: type: mozilla-foundation/common_voice_8_0 name: Common Voice hy-AM args: hy-AM metrics: - type: wer value: 10.811865729898516 name: WER LM - type: cer value: 2.2205361659079412 name: CER LM - task: name: Speech Recognition type: automatic-speech-recognition dataset: name: Robust Speech Event - Dev Data type: speech-recognition-community-v2/dev_data args: hy metrics: - name: Test WER type: wer value: 18.219363037089986 - name: Test CER type: cer value: 7.075988867335752 --- # This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the /WORKSPACE/DATA/HY/NOIZY_STUDENT_4/ - NA dataset. It achieves the following results on the evaluation set: - Loss: 0.1693 - Wer: 0.2373 - Cer: 0.0429 ## 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: 5e-05 - train_batch_size: 16 - eval_batch_size: 64 - seed: 842 - gradient_accumulation_steps: 8 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08 - lr_scheduler_type: cosine - lr_scheduler_warmup_ratio: 0.1 - training_steps: 5000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:-----:|:----:|:---------------:|:------:|:------:| | 1.255 | 7.24 | 500 | 0.2978 | 0.4294 | 0.0758 | | 1.0058 | 14.49 | 1000 | 0.1883 | 0.2838 | 0.0483 | | 0.9371 | 21.73 | 1500 | 0.1813 | 0.2627 | 0.0457 | | 0.8999 | 28.98 | 2000 | 0.1693 | 0.2373 | 0.0429 | | 0.8814 | 36.23 | 2500 | 0.1760 | 0.2420 | 0.0435 | | 0.8364 | 43.47 | 3000 | 0.1765 | 0.2416 | 0.0419 | | 0.8019 | 50.72 | 3500 | 0.1758 | 0.2311 | 0.0398 | | 0.7665 | 57.96 | 4000 | 0.1745 | 0.2240 | 0.0399 | | 0.7376 | 65.22 | 4500 | 0.1717 | 0.2190 | 0.0385 | | 0.716 | 72.46 | 5000 | 0.1700 | 0.2147 | 0.0382 | ### Framework versions - Transformers 4.17.0.dev0 - Pytorch 1.10.2 - Datasets 1.18.4.dev0 - Tokenizers 0.11.0