--- language: - hi license: apache-2.0 tags: - automatic-speech-recognition - mozilla-foundation/common_voice_7_0 - robust-speech-event - generated_from_trainer - hf-asr-leaderboard datasets: - mozilla-foundation/common_voice_7_0 model-index: - name: '' results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: Common Voice 7.0 type: mozilla-foundation/common_voice_7_0 args: hi metrics: - name: Test WER type: wer value: 38.18 --- # 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_7_0 - HI dataset. It achieves the following results on the evaluation set: - Loss: 0.7346 - Wer: 1.0479 ## 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 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - training_steps: 8000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | No log | 1.36 | 400 | 1.4595 | 1.0039 | | 4.7778 | 2.71 | 800 | 0.8082 | 1.0115 | | 0.6408 | 4.07 | 1200 | 0.7032 | 1.0079 | | 0.3937 | 5.42 | 1600 | 0.6889 | 1.0433 | | 0.3 | 6.78 | 2000 | 0.6820 | 1.0069 | | 0.3 | 8.14 | 2400 | 0.6670 | 1.0196 | | 0.226 | 9.49 | 2800 | 0.7216 | 1.0422 | | 0.197 | 10.85 | 3200 | 0.7669 | 1.0534 | | 0.165 | 12.2 | 3600 | 0.7517 | 1.0200 | | 0.1486 | 13.56 | 4000 | 0.7125 | 1.0357 | | 0.1486 | 14.92 | 4400 | 0.7447 | 1.0347 | | 0.122 | 16.27 | 4800 | 0.6899 | 1.0440 | | 0.1069 | 17.63 | 5200 | 0.7212 | 1.0350 | | 0.0961 | 18.98 | 5600 | 0.7417 | 1.0408 | | 0.086 | 20.34 | 6000 | 0.7402 | 1.0356 | | 0.086 | 21.69 | 6400 | 0.7761 | 1.0420 | | 0.0756 | 23.05 | 6800 | 0.7346 | 1.0369 | | 0.0666 | 24.41 | 7200 | 0.7506 | 1.0449 | | 0.0595 | 25.76 | 7600 | 0.7319 | 1.0476 | | 0.054 | 27.12 | 8000 | 0.7346 | 1.0479 | ### Framework versions - Transformers 4.16.0.dev0 - Pytorch 1.10.1+cu102 - Datasets 1.18.3 - Tokenizers 0.11.0