--- language: - tr license: apache-2.0 base_model: facebook/wav2vec2-large-xlsr-53 tags: - automatic-speech-recognition - common_voice - generated_from_trainer datasets: - common_voice metrics: - wer model-index: - name: wav2vec2-common_voice-tr-demo results: - task: name: Automatic Speech Recognition type: automatic-speech-recognition dataset: name: COMMON_VOICE - TR type: common_voice config: tr split: test args: 'Config: tr, Training split: train+validation, Eval split: test' metrics: - name: Wer type: wer value: 0.3428658972525789 --- # wav2vec2-common_voice-tr-demo This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set: - Loss: 0.3709 - Wer: 0.3429 ## 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: 15.0 ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | No log | 0.92 | 100 | 3.5988 | 1.0 | | No log | 1.83 | 200 | 3.0083 | 0.9999 | | No log | 2.75 | 300 | 0.8642 | 0.7579 | | No log | 3.67 | 400 | 0.5713 | 0.6203 | | 3.14 | 4.59 | 500 | 0.4795 | 0.5338 | | 3.14 | 5.5 | 600 | 0.4441 | 0.4912 | | 3.14 | 6.42 | 700 | 0.4241 | 0.4521 | | 3.14 | 7.34 | 800 | 0.4326 | 0.4611 | | 3.14 | 8.26 | 900 | 0.3913 | 0.4212 | | 0.2183 | 9.17 | 1000 | 0.4036 | 0.3973 | | 0.2183 | 10.09 | 1100 | 0.4035 | 0.3959 | | 0.2183 | 11.01 | 1200 | 0.3807 | 0.3790 | | 0.2183 | 11.93 | 1300 | 0.3750 | 0.3650 | | 0.2183 | 12.84 | 1400 | 0.3822 | 0.3573 | | 0.1011 | 13.76 | 1500 | 0.3747 | 0.3510 | | 0.1011 | 14.68 | 1600 | 0.3714 | 0.3454 | ### Framework versions - Transformers 4.32.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.0 - Tokenizers 0.13.3