--- library_name: transformers license: apache-2.0 base_model: facebook/wav2vec2-large-xlsr-53 tags: - generated_from_trainer metrics: - wer model-index: - name: xlsr-aiish-no results: [] --- # xlsr-aiish-no 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: 0.3093 ## 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 | |:-------------:|:-------:|:----:|:---------------:|:------:| | 4.5121 | 2.1505 | 200 | 2.5138 | 1.0 | | 1.2964 | 4.3011 | 400 | 0.1073 | 0.4756 | | 0.1795 | 6.4516 | 600 | 0.0381 | 0.3814 | | 0.096 | 8.6022 | 800 | 0.0067 | 0.3117 | | 0.0584 | 10.7527 | 1000 | 0.0140 | 0.3227 | | 0.0457 | 12.9032 | 1200 | 0.0039 | 0.3130 | | 0.0412 | 15.0538 | 1400 | 0.0024 | 0.3081 | | 0.0269 | 17.2043 | 1600 | 0.0142 | 0.3093 | | 0.0276 | 19.3548 | 1800 | 0.0013 | 0.3068 | | 0.0279 | 21.5054 | 2000 | 0.0044 | 0.3117 | | 0.0243 | 23.6559 | 2200 | 0.0026 | 0.3105 | | 0.0178 | 25.8065 | 2400 | 0.0006 | 0.3081 | | 0.0193 | 27.9570 | 2600 | 0.0115 | 0.3215 | | 0.0237 | 30.1075 | 2800 | 0.0008 | 0.3068 | | 0.0146 | 32.2581 | 3000 | 0.0011 | 0.3105 | | 0.0109 | 34.4086 | 3200 | 0.0002 | 0.3068 | | 0.0106 | 36.5591 | 3400 | 0.0011 | 0.3081 | | 0.0171 | 38.7097 | 3600 | 0.0012 | 0.3093 | | 0.0099 | 40.8602 | 3800 | 0.0002 | 0.3130 | | 0.0102 | 43.0108 | 4000 | 0.0014 | 0.3154 | | 0.0129 | 45.1613 | 4200 | 0.0003 | 0.3105 | | 0.0108 | 47.3118 | 4400 | 0.0001 | 0.3068 | | 0.0085 | 49.4624 | 4600 | 0.0001 | 0.3093 | | 0.0067 | 51.6129 | 4800 | 0.0001 | 0.3081 | | 0.0079 | 53.7634 | 5000 | 0.0006 | 0.3068 | | 0.0078 | 55.9140 | 5200 | 0.0001 | 0.3093 | | 0.0091 | 58.0645 | 5400 | 0.0020 | 0.3081 | | 0.0071 | 60.2151 | 5600 | 0.0017 | 0.3154 | | 0.004 | 62.3656 | 5800 | 0.0001 | 0.3105 | | 0.004 | 64.5161 | 6000 | 0.0001 | 0.3093 | | 0.0064 | 66.6667 | 6200 | 0.0096 | 0.3166 | | 0.0048 | 68.8172 | 6400 | 0.0000 | 0.3068 | | 0.0037 | 70.9677 | 6600 | 0.0321 | 0.3081 | | 0.0041 | 73.1183 | 6800 | 0.0000 | 0.3093 | | 0.0059 | 75.2688 | 7000 | 0.0013 | 0.3093 | | 0.0019 | 77.4194 | 7200 | 0.0011 | 0.3081 | | 0.0022 | 79.5699 | 7400 | 0.0000 | 0.3068 | | 0.0022 | 81.7204 | 7600 | 0.0000 | 0.3068 | | 0.004 | 83.8710 | 7800 | 0.0000 | 0.3081 | | 0.0025 | 86.0215 | 8000 | 0.0000 | 0.3081 | | 0.0032 | 88.1720 | 8200 | 0.0000 | 0.3081 | | 0.0019 | 90.3226 | 8400 | 0.0000 | 0.3093 | | 0.001 | 92.4731 | 8600 | 0.0000 | 0.3081 | | 0.001 | 94.6237 | 8800 | 0.0000 | 0.3093 | | 0.0018 | 96.7742 | 9000 | 0.0000 | 0.3093 | | 0.0019 | 98.9247 | 9200 | 0.0000 | 0.3093 | ### Framework versions - Transformers 4.45.0.dev0 - Pytorch 2.4.0 - Datasets 2.21.0 - Tokenizers 0.19.1