--- license: apache-2.0 tags: - generated_from_trainer datasets: - common_voice model-index: - name: xls-r-kyrgiz-cv8 results: [] --- # xls-r-kyrgiz-cv8 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: 0.5495 - Wer: 0.2951 - Cer: 0.0789 ## 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: 0.0001 - train_batch_size: 32 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 128 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 500 - num_epochs: 300.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:------:|:----:|:---------------:|:------:|:------:| | 3.1079 | 18.51 | 500 | 2.6795 | 0.9996 | 0.9825 | | 0.8506 | 37.04 | 1000 | 0.4323 | 0.3718 | 0.0961 | | 0.6821 | 55.55 | 1500 | 0.4105 | 0.3311 | 0.0878 | | 0.6091 | 74.07 | 2000 | 0.4281 | 0.3168 | 0.0851 | | 0.5429 | 92.58 | 2500 | 0.4525 | 0.3147 | 0.0842 | | 0.5063 | 111.11 | 3000 | 0.4619 | 0.3144 | 0.0839 | | 0.4661 | 129.62 | 3500 | 0.4660 | 0.3039 | 0.0818 | | 0.4353 | 148.15 | 4000 | 0.4695 | 0.3083 | 0.0820 | | 0.4048 | 166.65 | 4500 | 0.4909 | 0.3085 | 0.0824 | | 0.3852 | 185.18 | 5000 | 0.5074 | 0.3048 | 0.0812 | | 0.3567 | 203.69 | 5500 | 0.5111 | 0.3012 | 0.0810 | | 0.3451 | 222.22 | 6000 | 0.5225 | 0.2982 | 0.0804 | | 0.325 | 240.73 | 6500 | 0.5270 | 0.2955 | 0.0796 | | 0.3089 | 259.25 | 7000 | 0.5381 | 0.2929 | 0.0793 | | 0.2941 | 277.76 | 7500 | 0.5565 | 0.2923 | 0.0794 | | 0.2945 | 296.29 | 8000 | 0.5495 | 0.2951 | 0.0789 | ### Framework versions - Transformers 4.17.0.dev0 - Pytorch 1.10.2+cu102 - Datasets 1.18.3 - Tokenizers 0.11.0