--- license: apache-2.0 tags: - generated_from_trainer datasets: - common_voice model-index: - name: wav2vec2-large-xls-r-300m-turkish-colab_common_voice-8_4 results: [] --- # wav2vec2-large-xls-r-300m-turkish-colab_common_voice-8_4 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: 0.3201 - Wer: 0.3295 ## 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: 11 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-----:|:----:|:---------------:|:------:| | 5.9268 | 0.51 | 400 | 1.3204 | 0.9175 | | 0.7491 | 1.02 | 800 | 0.5880 | 0.6388 | | 0.4911 | 1.53 | 1200 | 0.4680 | 0.5613 | | 0.4265 | 2.04 | 1600 | 0.4213 | 0.5059 | | 0.3473 | 2.55 | 2000 | 0.4199 | 0.4955 | | 0.3291 | 3.07 | 2400 | 0.4323 | 0.5061 | | 0.2819 | 3.58 | 2800 | 0.4026 | 0.4490 | | 0.2628 | 4.09 | 3200 | 0.3831 | 0.4446 | | 0.2371 | 4.6 | 3600 | 0.3622 | 0.4234 | | 0.2274 | 5.11 | 4000 | 0.3473 | 0.4012 | | 0.2051 | 5.62 | 4400 | 0.3471 | 0.3998 | | 0.1985 | 6.13 | 4800 | 0.3759 | 0.4088 | | 0.1767 | 6.64 | 5200 | 0.3620 | 0.4012 | | 0.1707 | 7.15 | 5600 | 0.3415 | 0.3700 | | 0.1559 | 7.66 | 6000 | 0.3317 | 0.3661 | | 0.147 | 8.17 | 6400 | 0.3265 | 0.3618 | | 0.1339 | 8.68 | 6800 | 0.3293 | 0.3586 | | 0.126 | 9.2 | 7200 | 0.3386 | 0.3458 | | 0.1149 | 9.71 | 7600 | 0.3305 | 0.3397 | | 0.1051 | 10.22 | 8000 | 0.3235 | 0.3354 | | 0.1005 | 10.73 | 8400 | 0.3201 | 0.3295 | ### Framework versions - Transformers 4.11.3 - Pytorch 1.10.0+cu113 - Datasets 2.1.0 - Tokenizers 0.10.3