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--- |
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library_name: transformers |
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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-aiish-nomo |
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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-aiish-nomo |
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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: 0.3105 |
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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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| 4.5816 | 1.7167 | 200 | 2.5505 | 1.0 | |
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| 1.5977 | 3.4335 | 400 | 0.1411 | 0.5024 | |
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| 0.2835 | 5.1502 | 600 | 0.0321 | 0.3716 | |
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| 0.1323 | 6.8670 | 800 | 0.0247 | 0.3166 | |
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| 0.0826 | 8.5837 | 1000 | 0.0093 | 0.3289 | |
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| 0.0816 | 10.3004 | 1200 | 0.0032 | 0.3105 | |
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| 0.0543 | 12.0172 | 1400 | 0.0022 | 0.3130 | |
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| 0.0516 | 13.7339 | 1600 | 0.0045 | 0.3105 | |
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| 0.0399 | 15.4506 | 1800 | 0.0028 | 0.3130 | |
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| 0.0368 | 17.1674 | 2000 | 0.0099 | 0.3252 | |
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| 0.032 | 18.8841 | 2200 | 0.0007 | 0.3105 | |
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| 0.0349 | 20.6009 | 2400 | 0.0152 | 0.3240 | |
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| 0.025 | 22.3176 | 2600 | 0.0004 | 0.3105 | |
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| 0.0267 | 24.0343 | 2800 | 0.0003 | 0.3105 | |
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| 0.0279 | 25.7511 | 3000 | 0.0003 | 0.3105 | |
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| 0.0231 | 27.4678 | 3200 | 0.0014 | 0.3142 | |
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| 0.0311 | 29.1845 | 3400 | 0.0005 | 0.3105 | |
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| 0.0209 | 30.9013 | 3600 | 0.0015 | 0.3105 | |
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| 0.0175 | 32.6180 | 3800 | 0.0023 | 0.3105 | |
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| 0.0158 | 34.3348 | 4000 | 0.0002 | 0.3105 | |
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| 0.0189 | 36.0515 | 4200 | 0.0004 | 0.3105 | |
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| 0.0137 | 37.7682 | 4400 | 0.0001 | 0.3105 | |
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| 0.0138 | 39.4850 | 4600 | 0.0002 | 0.3105 | |
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| 0.0141 | 41.2017 | 4800 | 0.0002 | 0.3105 | |
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| 0.0147 | 42.9185 | 5000 | 0.0011 | 0.3105 | |
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| 0.013 | 44.6352 | 5200 | 0.0020 | 0.3130 | |
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| 0.0204 | 46.3519 | 5400 | 0.0011 | 0.3154 | |
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| 0.0131 | 48.0687 | 5600 | 0.0018 | 0.3117 | |
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| 0.0109 | 49.7854 | 5800 | 0.0053 | 0.3105 | |
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| 0.0135 | 51.5021 | 6000 | 0.0038 | 0.3068 | |
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| 0.0112 | 53.2189 | 6200 | 0.0003 | 0.3081 | |
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| 0.0075 | 54.9356 | 6400 | 0.0001 | 0.3081 | |
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| 0.0116 | 56.6524 | 6600 | 0.0001 | 0.3068 | |
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| 0.0048 | 58.3691 | 6800 | 0.0013 | 0.3093 | |
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| 0.0077 | 60.0858 | 7000 | 0.0000 | 0.3081 | |
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| 0.009 | 61.8026 | 7200 | 0.0002 | 0.3081 | |
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| 0.0043 | 63.5193 | 7400 | 0.0001 | 0.3081 | |
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| 0.0043 | 65.2361 | 7600 | 0.0017 | 0.3093 | |
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| 0.0063 | 66.9528 | 7800 | 0.0000 | 0.3081 | |
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| 0.0051 | 68.6695 | 8000 | 0.0000 | 0.3081 | |
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| 0.0062 | 70.3863 | 8200 | 0.0001 | 0.3081 | |
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| 0.0027 | 72.1030 | 8400 | 0.0000 | 0.3081 | |
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| 0.0043 | 73.8197 | 8600 | 0.0000 | 0.3068 | |
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| 0.0031 | 75.5365 | 8800 | 0.0000 | 0.3081 | |
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| 0.004 | 77.2532 | 9000 | 0.0001 | 0.3081 | |
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| 0.0045 | 78.9700 | 9200 | 0.0000 | 0.3093 | |
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| 0.0049 | 80.6867 | 9400 | 0.0000 | 0.3081 | |
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| 0.0026 | 82.4034 | 9600 | 0.0001 | 0.3093 | |
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| 0.0025 | 84.1202 | 9800 | 0.0000 | 0.3081 | |
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| 0.0029 | 85.8369 | 10000 | 0.0000 | 0.3093 | |
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| 0.0025 | 87.5536 | 10200 | 0.0000 | 0.3105 | |
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| 0.0029 | 89.2704 | 10400 | 0.0000 | 0.3105 | |
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| 0.0018 | 90.9871 | 10600 | 0.0000 | 0.3105 | |
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| 0.0027 | 92.7039 | 10800 | 0.0000 | 0.3105 | |
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| 0.0025 | 94.4206 | 11000 | 0.0000 | 0.3105 | |
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| 0.0014 | 96.1373 | 11200 | 0.0000 | 0.3105 | |
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| 0.0021 | 97.8541 | 11400 | 0.0000 | 0.3105 | |
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| 0.0016 | 99.5708 | 11600 | 0.0000 | 0.3105 | |
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### Framework versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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