--- language: - hi license: apache-2.0 base_model: facebook/wav2vec2-large-xlsr-53 tags: - automatic-speech-recognition - mozilla-foundation/common_voice_15_0 - mms - generated_from_trainer datasets: - common_voice_15_0 metrics: - wer model-index: - name: Output results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: MOZILLA-FOUNDATION/COMMON_VOICE_15_0 - HI type: common_voice_15_0 config: hi split: validation args: 'Config: hi, Training split: train, Eval split: validation' metrics: - name: Wer type: wer value: 1.0016248153618907 --- # Output This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the MOZILLA-FOUNDATION/COMMON_VOICE_15_0 - HI dataset. It achieves the following results on the evaluation set: - Loss: 20.2289 - Wer: 1.0016 ## 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 - 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: 500 - num_epochs: 1.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:------:|:----:|:---------------:|:------:| | No log | 0.6897 | 100 | 21.9162 | 1.0003 | ### Framework versions - Transformers 4.42.0.dev0 - Pytorch 2.3.0 - Datasets 2.19.1 - Tokenizers 0.19.1