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--- |
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language: |
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- tr |
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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: phoneme_test_3_tr |
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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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# Wav2vec2-xls-r-phoneme-300m-tr |
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This model is a fine-tuned version of [wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the COMMON_VOICE - TR dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6380 |
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- Wer: 0.1664 |
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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: 0.0005 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 32 |
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- total_eval_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: 500 |
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- num_epochs: 20.0 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 13.6687 | 0.92 | 100 | 12.4567 | 1.0 | |
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| 3.4219 | 1.83 | 200 | 3.4704 | 1.0 | |
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| 3.1846 | 2.75 | 300 | 3.2281 | 0.9935 | |
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| 2.0076 | 3.67 | 400 | 1.7415 | 0.5222 | |
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| 1.0244 | 4.59 | 500 | 1.0290 | 0.3323 | |
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| 0.7095 | 5.5 | 600 | 0.8424 | 0.2859 | |
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| 0.619 | 6.42 | 700 | 0.7389 | 0.2232 | |
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| 0.3541 | 7.34 | 800 | 0.7049 | 0.2043 | |
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| 0.2946 | 8.26 | 900 | 0.7065 | 0.2153 | |
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| 0.2868 | 9.17 | 1000 | 0.6840 | 0.2115 | |
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| 0.2245 | 10.09 | 1100 | 0.6714 | 0.1952 | |
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| 0.1394 | 11.01 | 1200 | 0.6864 | 0.1954 | |
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| 0.1288 | 11.93 | 1300 | 0.6696 | 0.2017 | |
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| 0.1568 | 12.84 | 1400 | 0.6468 | 0.1843 | |
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| 0.1269 | 13.76 | 1500 | 0.6736 | 0.1965 | |
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| 0.1101 | 14.68 | 1600 | 0.6689 | 0.1915 | |
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| 0.1388 | 15.6 | 1700 | 0.6690 | 0.1782 | |
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| 0.0739 | 16.51 | 1800 | 0.6364 | 0.1734 | |
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| 0.0897 | 17.43 | 1900 | 0.6480 | 0.1748 | |
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| 0.0795 | 18.35 | 2000 | 0.6356 | 0.1695 | |
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| 0.0823 | 19.27 | 2100 | 0.6382 | 0.1685 | |
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### Framework versions |
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- Transformers 4.13.0.dev0 |
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- Pytorch 1.8.1 |
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- Datasets 1.16.2.dev0 |
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- Tokenizers 0.10.3 |
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