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--- |
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language: |
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- tr |
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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: wav2vec2-large-xls-r-300m-common_voice-tr-ft |
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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-large-xls-r-300m-common_voice-tr-ft |
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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 - TR dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3644 |
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- Wer: 0.3394 |
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- Cer: 0.0811 |
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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: 0.0003 |
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- train_batch_size: 4 |
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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: 8 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 64 |
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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: 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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| 1.6613 | 4.59 | 500 | 0.8079 | 0.8542 | 0.2504 | |
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| 1.3496 | 9.17 | 1000 | 0.4729 | 0.5968 | 0.1518 | |
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| 1.1003 | 13.76 | 1500 | 0.4106 | 0.5225 | 0.1357 | |
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| 1.1532 | 18.35 | 2000 | 0.3957 | 0.4978 | 0.1256 | |
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| 1.0305 | 22.94 | 2500 | 0.3764 | 0.5008 | 0.1291 | |
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| 0.8303 | 27.52 | 3000 | 0.3826 | 0.5113 | 0.1292 | |
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| 0.9115 | 32.11 | 3500 | 0.3819 | 0.4324 | 0.1070 | |
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| 0.8193 | 36.7 | 4000 | 0.3694 | 0.4223 | 0.1036 | |
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| 0.8948 | 41.28 | 4500 | 0.3714 | 0.4100 | 0.1005 | |
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| 0.774 | 45.87 | 5000 | 0.3558 | 0.3923 | 0.0971 | |
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| 0.8194 | 50.46 | 5500 | 0.3729 | 0.4603 | 0.1180 | |
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| 0.8616 | 55.05 | 6000 | 0.3616 | 0.3908 | 0.0963 | |
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| 0.7901 | 59.63 | 6500 | 0.3575 | 0.3837 | 0.0952 | |
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| 0.778 | 64.22 | 7000 | 0.3732 | 0.3790 | 0.0928 | |
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| 0.7238 | 68.81 | 7500 | 0.3674 | 0.3734 | 0.0904 | |
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| 0.6985 | 73.39 | 8000 | 0.3627 | 0.3615 | 0.0863 | |
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| 0.5889 | 77.98 | 8500 | 0.3705 | 0.3548 | 0.0858 | |
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| 0.5447 | 82.57 | 9000 | 0.3678 | 0.3534 | 0.0854 | |
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| 0.4763 | 87.16 | 9500 | 0.3627 | 0.3509 | 0.0840 | |
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| 0.3544 | 91.74 | 10000 | 0.3690 | 0.3495 | 0.0834 | |
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| 0.4879 | 96.33 | 10500 | 0.3683 | 0.3418 | 0.0820 | |
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### Framework versions |
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- Transformers 4.13.0.dev0 |
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- Pytorch 1.9.0+cu111 |
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- Datasets 1.15.2.dev0 |
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- Tokenizers 0.10.3 |
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