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Kuray107
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librispeech-100h-supervised

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
Generated from Trainer
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: librispeech-100h-supervised
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+ results: []
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+ ---
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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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+ # librispeech-100h-supervised
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-large-lv60](https://huggingface.co/facebook/wav2vec2-large-lv60) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0955
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+ - Wer: 0.0345
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 24
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+ - eval_batch_size: 8
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+ - seed: 42
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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: 1000
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+ - num_epochs: 15
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 4.8277 | 0.42 | 500 | 2.9071 | 1.0 |
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+ | 2.0261 | 0.84 | 1000 | 0.3060 | 0.2496 |
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+ | 0.2181 | 1.26 | 1500 | 0.1172 | 0.0873 |
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+ | 0.1255 | 1.68 | 2000 | 0.0894 | 0.0637 |
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+ | 0.0971 | 2.1 | 2500 | 0.0821 | 0.0560 |
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+ | 0.078 | 2.52 | 3000 | 0.0751 | 0.0500 |
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+ | 0.0706 | 2.94 | 3500 | 0.0721 | 0.0456 |
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+ | 0.0609 | 3.36 | 4000 | 0.0755 | 0.0464 |
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+ | 0.0572 | 3.78 | 4500 | 0.0705 | 0.0431 |
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+ | 0.0528 | 4.2 | 5000 | 0.0715 | 0.0423 |
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+ | 0.0481 | 4.62 | 5500 | 0.0691 | 0.0403 |
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+ | 0.0471 | 5.04 | 6000 | 0.0743 | 0.0401 |
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+ | 0.0412 | 5.46 | 6500 | 0.0757 | 0.0399 |
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+ | 0.0416 | 5.88 | 7000 | 0.0688 | 0.0378 |
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+ | 0.0391 | 6.3 | 7500 | 0.0704 | 0.0383 |
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+ | 0.0367 | 6.72 | 8000 | 0.0742 | 0.0387 |
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+ | 0.0349 | 7.14 | 8500 | 0.0732 | 0.0388 |
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+ | 0.033 | 7.56 | 9000 | 0.0719 | 0.0374 |
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+ | 0.0327 | 7.98 | 9500 | 0.0750 | 0.0369 |
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+ | 0.0292 | 8.4 | 10000 | 0.0734 | 0.0368 |
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+ | 0.0303 | 8.82 | 10500 | 0.0733 | 0.0365 |
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+ | 0.0283 | 9.24 | 11000 | 0.0766 | 0.0357 |
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+ | 0.0269 | 9.66 | 11500 | 0.0761 | 0.0350 |
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+ | 0.0268 | 10.08 | 12000 | 0.0802 | 0.0359 |
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+ | 0.0245 | 10.42 | 12500 | 0.0758 | 0.0354 |
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+ | 0.023 | 10.84 | 13000 | 0.0775 | 0.0349 |
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+ | 0.0186 | 11.26 | 13500 | 0.0817 | 0.0355 |
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+ | 0.0176 | 11.68 | 14000 | 0.0853 | 0.0354 |
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+ | 0.0163 | 12.1 | 14500 | 0.0880 | 0.0347 |
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+ | 0.0156 | 12.52 | 15000 | 0.0864 | 0.0357 |
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+ | 0.0141 | 12.94 | 15500 | 0.0897 | 0.0355 |
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+ | 0.0134 | 13.36 | 16000 | 0.0915 | 0.0349 |
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+ | 0.013 | 13.78 | 16500 | 0.0928 | 0.0350 |
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+ | 0.0097 | 13.42 | 17000 | 0.0955 | 0.0345 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.14.1
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+ - Pytorch 1.10.2
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+ - Datasets 1.18.2
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+ - Tokenizers 0.10.3