--- language: - ja license: apache-2.0 tags: - automatic-speech-recognition - vumichien/common_voice_large_jsut_jsss_css10 - generated_from_trainer model-index: - name: wav2vec2-xls-r-1b-ja-dumy8 results: [] --- # wav2vec2-xls-r-1b-ja-dumy8 This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the VUMICHIEN/COMMON_VOICE_LARGE_JSUT_JSSS_CSS10 - JA dataset. It achieves the following results on the evaluation set: - Loss: 0.2104 - Wer: 0.1941 - Cer: 0.0991 ## 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: 5e-05 - train_batch_size: 16 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 4 - total_train_batch_size: 64 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 1000 - num_epochs: 100.0 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| | 2.2896 | 3.37 | 1500 | 0.4748 | 0.4013 | 0.1767 | | 1.1608 | 6.74 | 3000 | 0.3350 | 0.3159 | 0.1456 | | 1.1042 | 10.11 | 4500 | 0.3119 | 0.2971 | 0.1400 | | 1.0494 | 13.48 | 6000 | 0.2974 | 0.2867 | 0.1353 | | 1.0061 | 16.85 | 7500 | 0.2802 | 0.2746 | 0.1300 | | 0.9629 | 20.22 | 9000 | 0.2844 | 0.2776 | 0.1326 | | 0.9267 | 23.59 | 10500 | 0.2577 | 0.2603 | 0.1255 | | 0.8984 | 26.96 | 12000 | 0.2508 | 0.2531 | 0.1226 | | 0.8729 | 30.34 | 13500 | 0.2629 | 0.2606 | 0.1254 | | 0.8546 | 33.71 | 15000 | 0.2402 | 0.2447 | 0.1193 | | 0.8304 | 37.08 | 16500 | 0.2532 | 0.2472 | 0.1209 | | 0.8075 | 40.45 | 18000 | 0.2439 | 0.2469 | 0.1198 | | 0.7827 | 43.82 | 19500 | 0.2387 | 0.2372 | 0.1167 | | 0.7627 | 47.19 | 21000 | 0.2344 | 0.2331 | 0.1147 | | 0.7402 | 50.56 | 22500 | 0.2314 | 0.2299 | 0.1135 | | 0.718 | 53.93 | 24000 | 0.2257 | 0.2267 | 0.1114 | | 0.7016 | 57.3 | 25500 | 0.2204 | 0.2184 | 0.1089 | | 0.6804 | 60.67 | 27000 | 0.2227 | 0.2181 | 0.1085 | | 0.6625 | 64.04 | 28500 | 0.2138 | 0.2112 | 0.1058 | | 0.6465 | 67.42 | 30000 | 0.2141 | 0.2081 | 0.1044 | | 0.6238 | 70.79 | 31500 | 0.2172 | 0.2082 | 0.1050 | | 0.6062 | 74.16 | 33000 | 0.2174 | 0.2058 | 0.1043 | | 0.588 | 77.53 | 34500 | 0.2156 | 0.2034 | 0.1027 | | 0.5722 | 80.9 | 36000 | 0.2162 | 0.2032 | 0.1029 | | 0.5585 | 84.27 | 37500 | 0.2156 | 0.2022 | 0.1021 | | 0.5456 | 87.64 | 39000 | 0.2126 | 0.1993 | 0.1009 | | 0.5325 | 91.01 | 40500 | 0.2121 | 0.1966 | 0.1003 | | 0.5229 | 94.38 | 42000 | 0.2104 | 0.1941 | 0.0991 | | 0.5134 | 97.75 | 43500 | 0.2108 | 0.1948 | 0.0992 | ### Framework versions - Transformers 4.16.0.dev0 - Pytorch 1.10.1+cu102 - Datasets 1.17.1.dev0 - Tokenizers 0.11.0