update readme.md
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README.md
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@@ -45,8 +45,36 @@ model = Wav2Vec2ForCTC.from_pretrained("emre/wav2vec-tr-lite-AG")
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resampler = torchaudio.transforms.Resample(48_000, 16_000)
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resampler = torchaudio.transforms.Resample(48_000, 16_000)
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.00005
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- train_batch_size: 2
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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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- gradient_accumulation_steps: 8
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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: 30.0
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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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| 0.4388 | 3.7 | 400 | 1.366 | 0.9701 |
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| 0.3766 | 7.4 | 800 | 0.4914 | 0.5374 |
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| 0.2295 | 11.11 | 1200 | 0.3934 | 0.4125 |
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| 0.1121 | 14.81 | 1600 | 0.3264 | 0.2904 |
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| 0.1473 | 18.51 | 2000 | 0.3103 | 0.2671 |
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| 0.1013 | 22.22 | 2400 | 0.2589 | 0.2324 |
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| 0.0704 | 25.92 | 2800 | 0.2826 | 0.2339 |
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| 0.0537 | 29.63 | 3200 | 0.2704 | 0.2309 |
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### Framework versions
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- Transformers 4.12.0.dev0
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- Pytorch 1.8.1
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- Datasets 1.14.1.dev0
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- Tokenizers 0.10.3
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