--- license: apache-2.0 base_model: facebook/wav2vec2-xls-r-300m tags: - generated_from_trainer datasets: - common_voice metrics: - wer model-index: - name: wav2vec2-large-xls-r-300m-turkish-colab results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: common_voice type: common_voice config: tr split: test args: tr metrics: - name: Wer type: wer value: 0.6933797909407665 --- # wav2vec2-large-xls-r-300m-turkish-colab This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co./facebook/wav2vec2-xls-r-300m) on the common_voice dataset. It achieves the following results on the evaluation set: - Loss: 0.6890 - Wer: 0.6934 ## 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: 200 - num_epochs: 30 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 6.5704 | 5.71 | 100 | 3.2378 | 1.0 | | 3.0747 | 11.43 | 200 | 2.9447 | 1.0 | | 1.4169 | 17.14 | 300 | 0.8814 | 0.8728 | | 0.3139 | 22.86 | 400 | 0.7375 | 0.7021 | | 0.1823 | 28.57 | 500 | 0.6890 | 0.6934 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 1.18.3 - Tokenizers 0.13.3