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--- |
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language: |
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- zh-TW |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- common_voice |
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- generated_from_trainer |
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datasets: |
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- common_voice |
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model-index: |
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- name: '' |
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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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# |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the COMMON_VOICE - ZH-TW dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1786 |
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- Wer: 0.8594 |
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- Cer: 0.2964 |
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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: 7.5e-05 |
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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: 4 |
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- total_train_batch_size: 32 |
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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: 2000 |
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- num_epochs: 100.0 |
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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 | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
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| 64.6189 | 2.51 | 500 | 63.8077 | 1.0 | 1.0 | |
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| 8.0561 | 5.03 | 1000 | 6.8014 | 1.0 | 1.0 | |
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| 6.0427 | 7.54 | 1500 | 6.0745 | 1.0 | 1.0 | |
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| 5.9357 | 10.05 | 2000 | 5.8682 | 1.0 | 1.0 | |
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| 5.0489 | 12.56 | 2500 | 4.4032 | 0.9990 | 0.7750 | |
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| 4.6184 | 15.08 | 3000 | 3.8383 | 0.9983 | 0.6768 | |
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| 4.365 | 17.59 | 3500 | 3.4633 | 0.9959 | 0.6299 | |
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| 4.1026 | 20.1 | 4000 | 3.0732 | 0.9902 | 0.5814 | |
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| 3.8655 | 22.61 | 4500 | 2.7638 | 0.9868 | 0.5465 | |
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| 3.6991 | 25.13 | 5000 | 2.4759 | 0.9811 | 0.5088 | |
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| 3.4894 | 27.64 | 5500 | 2.2937 | 0.9746 | 0.4852 | |
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| 3.3983 | 30.15 | 6000 | 2.1684 | 0.9733 | 0.4674 | |
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| 3.2736 | 32.66 | 6500 | 2.0372 | 0.9659 | 0.4458 | |
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| 3.1884 | 35.18 | 7000 | 1.9267 | 0.9648 | 0.4329 | |
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| 3.1248 | 37.69 | 7500 | 1.8408 | 0.9591 | 0.4217 | |
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| 3.0381 | 40.2 | 8000 | 1.7531 | 0.9503 | 0.4074 | |
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| 2.9515 | 42.71 | 8500 | 1.6880 | 0.9459 | 0.3967 | |
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| 2.8704 | 45.23 | 9000 | 1.6264 | 0.9378 | 0.3884 | |
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| 2.8128 | 47.74 | 9500 | 1.5621 | 0.9341 | 0.3782 | |
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| 2.7386 | 50.25 | 10000 | 1.5011 | 0.9243 | 0.3664 | |
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| 2.6646 | 52.76 | 10500 | 1.4608 | 0.9192 | 0.3575 | |
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| 2.6072 | 55.28 | 11000 | 1.4251 | 0.9148 | 0.3501 | |
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| 2.569 | 57.79 | 11500 | 1.3837 | 0.9060 | 0.3462 | |
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| 2.5091 | 60.3 | 12000 | 1.3589 | 0.9070 | 0.3392 | |
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| 2.4588 | 62.81 | 12500 | 1.3261 | 0.8966 | 0.3284 | |
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| 2.4083 | 65.33 | 13000 | 1.3052 | 0.8982 | 0.3265 | |
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| 2.3787 | 67.84 | 13500 | 1.2997 | 0.8908 | 0.3243 | |
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| 2.3457 | 70.35 | 14000 | 1.2778 | 0.8898 | 0.3187 | |
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| 2.3099 | 72.86 | 14500 | 1.2661 | 0.8830 | 0.3172 | |
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| 2.2559 | 75.38 | 15000 | 1.2475 | 0.8851 | 0.3143 | |
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| 2.2264 | 77.89 | 15500 | 1.2319 | 0.8739 | 0.3085 | |
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| 2.196 | 80.4 | 16000 | 1.2218 | 0.8722 | 0.3049 | |
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| 2.1613 | 82.91 | 16500 | 1.2093 | 0.8719 | 0.3051 | |
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| 2.1455 | 85.43 | 17000 | 1.2055 | 0.8624 | 0.3005 | |
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| 2.1193 | 87.94 | 17500 | 1.1975 | 0.8600 | 0.2982 | |
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| 2.0911 | 90.45 | 18000 | 1.1960 | 0.8648 | 0.3003 | |
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| 2.0884 | 92.96 | 18500 | 1.1871 | 0.8638 | 0.2971 | |
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| 2.0766 | 95.48 | 19000 | 1.1814 | 0.8617 | 0.2967 | |
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| 2.0735 | 97.99 | 19500 | 1.1801 | 0.8621 | 0.2969 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.2.dev0 |
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- Tokenizers 0.11.0 |
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