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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: xlsr-big-kinnn |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# xlsr-big-kinnn |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0000 |
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- Wer: 0.0510 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0004 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 132 |
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- num_epochs: 100 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:| |
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| 2.0626 | 2.1505 | 200 | 0.6872 | 0.5597 | |
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| 0.3624 | 4.3011 | 400 | 0.0468 | 0.1067 | |
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| 0.106 | 6.4516 | 600 | 0.0157 | 0.0641 | |
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| 0.0637 | 8.6022 | 800 | 0.0137 | 0.0625 | |
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| 0.0448 | 10.7527 | 1000 | 0.0086 | 0.0699 | |
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| 0.03 | 12.9032 | 1200 | 0.0027 | 0.0523 | |
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| 0.0264 | 15.0538 | 1400 | 0.0072 | 0.0559 | |
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| 0.0265 | 17.2043 | 1600 | 0.0042 | 0.0543 | |
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| 0.0266 | 19.3548 | 1800 | 0.0018 | 0.0553 | |
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| 0.0199 | 21.5054 | 2000 | 0.0083 | 0.0766 | |
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| 0.0139 | 23.6559 | 2200 | 0.0021 | 0.0569 | |
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| 0.0154 | 25.8065 | 2400 | 0.0033 | 0.0545 | |
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| 0.0145 | 27.9570 | 2600 | 0.0005 | 0.0510 | |
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| 0.0153 | 30.1075 | 2800 | 0.0017 | 0.0539 | |
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| 0.0144 | 32.2581 | 3000 | 0.0002 | 0.0527 | |
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| 0.0118 | 34.4086 | 3200 | 0.0024 | 0.0836 | |
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| 0.0118 | 36.5591 | 3400 | 0.0012 | 0.0575 | |
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| 0.0149 | 38.7097 | 3600 | 0.0046 | 0.0583 | |
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| 0.0125 | 40.8602 | 3800 | 0.0005 | 0.0571 | |
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| 0.0108 | 43.0108 | 4000 | 0.0003 | 0.0615 | |
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| 0.011 | 45.1613 | 4200 | 0.0010 | 0.0585 | |
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| 0.0085 | 47.3118 | 4400 | 0.0002 | 0.0510 | |
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| 0.0082 | 49.4624 | 4600 | 0.0003 | 0.0571 | |
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| 0.0076 | 51.6129 | 4800 | 0.0004 | 0.0607 | |
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| 0.0065 | 53.7634 | 5000 | 0.0001 | 0.0553 | |
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| 0.0058 | 55.9140 | 5200 | 0.0006 | 0.0512 | |
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| 0.0069 | 58.0645 | 5400 | 0.0020 | 0.0539 | |
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| 0.0046 | 60.2151 | 5600 | 0.0001 | 0.0537 | |
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| 0.0049 | 62.3656 | 5800 | 0.0001 | 0.0577 | |
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| 0.0038 | 64.5161 | 6000 | 0.0000 | 0.0615 | |
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| 0.0033 | 66.6667 | 6200 | 0.0000 | 0.0703 | |
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| 0.0048 | 68.8172 | 6400 | 0.0002 | 0.0711 | |
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| 0.0039 | 70.9677 | 6600 | 0.0000 | 0.0520 | |
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| 0.0048 | 73.1183 | 6800 | 0.0003 | 0.0523 | |
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| 0.0021 | 75.2688 | 7000 | 0.0001 | 0.0516 | |
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| 0.0024 | 77.4194 | 7200 | 0.0000 | 0.0510 | |
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| 0.0027 | 79.5699 | 7400 | 0.0000 | 0.0508 | |
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| 0.0014 | 81.7204 | 7600 | 0.0000 | 0.0504 | |
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| 0.0022 | 83.8710 | 7800 | 0.0000 | 0.0506 | |
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| 0.0019 | 86.0215 | 8000 | 0.0000 | 0.0520 | |
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| 0.0022 | 88.1720 | 8200 | 0.0000 | 0.0510 | |
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| 0.001 | 90.3226 | 8400 | 0.0000 | 0.0510 | |
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| 0.0012 | 92.4731 | 8600 | 0.0000 | 0.0510 | |
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| 0.0011 | 94.6237 | 8800 | 0.0000 | 0.0510 | |
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| 0.0014 | 96.7742 | 9000 | 0.0000 | 0.0510 | |
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| 0.0008 | 98.9247 | 9200 | 0.0000 | 0.0510 | |
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### Framework versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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