--- library_name: transformers license: apache-2.0 base_model: facebook/wav2vec2-large-xlsr-53 tags: - generated_from_trainer metrics: - wer model-index: - name: xlsr-nomimosev-aiish results: [] --- # xlsr-nomimosev-aiish This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0000 - Wer: 0.0 ## 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: 0.0004 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - gradient_accumulation_steps: 2 - total_train_batch_size: 16 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_steps: 132 - num_epochs: 100 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Wer | |:-------------:|:-------:|:-----:|:---------------:|:------:| | 4.8467 | 1.2945 | 200 | 2.8108 | 1.0 | | 2.6337 | 2.5890 | 400 | 2.0411 | 1.0 | | 1.2205 | 3.8835 | 600 | 0.1323 | 0.4010 | | 0.3704 | 5.1780 | 800 | 0.0457 | 0.1907 | | 0.2019 | 6.4725 | 1000 | 0.0216 | 0.1748 | | 0.158 | 7.7670 | 1200 | 0.0050 | 0.1027 | | 0.1039 | 9.0615 | 1400 | 0.0018 | 0.0134 | | 0.0988 | 10.3560 | 1600 | 0.0116 | 0.0159 | | 0.0758 | 11.6505 | 1800 | 0.0061 | 0.0110 | | 0.0681 | 12.9450 | 2000 | 0.0068 | 0.0208 | | 0.0549 | 14.2395 | 2200 | 0.0022 | 0.0232 | | 0.0622 | 15.5340 | 2400 | 0.0005 | 0.0355 | | 0.0507 | 16.8285 | 2600 | 0.0018 | 0.0061 | | 0.0442 | 18.1230 | 2800 | 0.0005 | 0.0012 | | 0.044 | 19.4175 | 3000 | 0.0032 | 0.0037 | | 0.0428 | 20.7120 | 3200 | 0.0025 | 0.0098 | | 0.04 | 22.0065 | 3400 | 0.0253 | 0.0660 | | 0.0385 | 23.3010 | 3600 | 0.0008 | 0.0098 | | 0.0333 | 24.5955 | 3800 | 0.0003 | 0.0 | | 0.0289 | 25.8900 | 4000 | 0.0002 | 0.0 | | 0.0225 | 27.1845 | 4200 | 0.0031 | 0.0587 | | 0.0275 | 28.4790 | 4400 | 0.0006 | 0.0220 | | 0.0275 | 29.7735 | 4600 | 0.0005 | 0.0086 | | 0.0295 | 31.0680 | 4800 | 0.0003 | 0.0073 | | 0.0281 | 32.3625 | 5000 | 0.0002 | 0.0061 | | 0.0254 | 33.6570 | 5200 | 0.0005 | 0.0269 | | 0.0229 | 34.9515 | 5400 | 0.0022 | 0.0330 | | 0.0203 | 36.2460 | 5600 | 0.0009 | 0.0147 | | 0.0224 | 37.5405 | 5800 | 0.0001 | 0.0 | | 0.0176 | 38.8350 | 6000 | 0.0001 | 0.0086 | | 0.0204 | 40.1294 | 6200 | 0.0004 | 0.0073 | | 0.0172 | 41.4239 | 6400 | 0.0004 | 0.0037 | | 0.0157 | 42.7184 | 6600 | 0.0001 | 0.0 | | 0.0157 | 44.0129 | 6800 | 0.0001 | 0.0 | | 0.0146 | 45.3074 | 7000 | 0.0001 | 0.0012 | | 0.0105 | 46.6019 | 7200 | 0.0001 | 0.0012 | | 0.0122 | 47.8964 | 7400 | 0.0001 | 0.0 | | 0.014 | 49.1909 | 7600 | 0.0004 | 0.0012 | | 0.0187 | 50.4854 | 7800 | 0.0001 | 0.0024 | | 0.0105 | 51.7799 | 8000 | 0.0004 | 0.0024 | | 0.0094 | 53.0744 | 8200 | 0.0059 | 0.0037 | | 0.0082 | 54.3689 | 8400 | 0.0000 | 0.0 | | 0.0106 | 55.6634 | 8600 | 0.0077 | 0.0159 | | 0.0082 | 56.9579 | 8800 | 0.0000 | 0.0049 | | 0.0085 | 58.2524 | 9000 | 0.0000 | 0.0134 | | 0.0054 | 59.5469 | 9200 | 0.0000 | 0.0049 | | 0.0077 | 60.8414 | 9400 | 0.0000 | 0.0122 | | 0.0098 | 62.1359 | 9600 | 0.0000 | 0.0061 | | 0.0094 | 63.4304 | 9800 | 0.0000 | 0.0049 | | 0.0069 | 64.7249 | 10000 | 0.0001 | 0.0012 | | 0.0081 | 66.0194 | 10200 | 0.0000 | 0.0 | | 0.006 | 67.3139 | 10400 | 0.0001 | 0.0 | | 0.0061 | 68.6084 | 10600 | 0.0004 | 0.0024 | | 0.005 | 69.9029 | 10800 | 0.0000 | 0.0 | | 0.0055 | 71.1974 | 11000 | 0.0010 | 0.0037 | | 0.0053 | 72.4919 | 11200 | 0.0001 | 0.0012 | | 0.0057 | 73.7864 | 11400 | 0.0000 | 0.0061 | | 0.0064 | 75.0809 | 11600 | 0.0001 | 0.0012 | | 0.0068 | 76.3754 | 11800 | 0.0000 | 0.0012 | | 0.0055 | 77.6699 | 12000 | 0.0019 | 0.0134 | | 0.0068 | 78.9644 | 12200 | 0.0008 | 0.0073 | | 0.0045 | 80.2589 | 12400 | 0.0000 | 0.0061 | | 0.0032 | 81.5534 | 12600 | 0.0000 | 0.0073 | | 0.0038 | 82.8479 | 12800 | 0.0000 | 0.0 | | 0.0028 | 84.1424 | 13000 | 0.0000 | 0.0037 | | 0.004 | 85.4369 | 13200 | 0.0000 | 0.0 | | 0.0027 | 86.7314 | 13400 | 0.0000 | 0.0 | | 0.0019 | 88.0259 | 13600 | 0.0000 | 0.0 | | 0.0019 | 89.3204 | 13800 | 0.0000 | 0.0 | | 0.0019 | 90.6149 | 14000 | 0.0000 | 0.0 | | 0.0016 | 91.9094 | 14200 | 0.0000 | 0.0 | | 0.0016 | 93.2039 | 14400 | 0.0000 | 0.0012 | | 0.0015 | 94.4984 | 14600 | 0.0000 | 0.0 | | 0.0013 | 95.7929 | 14800 | 0.0000 | 0.0 | | 0.0023 | 97.0874 | 15000 | 0.0000 | 0.0 | | 0.0017 | 98.3819 | 15200 | 0.0000 | 0.0 | | 0.0018 | 99.6764 | 15400 | 0.0000 | 0.0 | ### Framework versions - Transformers 4.45.0.dev0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1