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wav2vec2-base-timit-demo-google-colab

Automatic Speech Recognition
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wav2vec2
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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: wav2vec2-base-timit-demo-google-colab
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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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+ # wav2vec2-base-timit-demo-google-colab
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5237
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+ - Wer: 0.3346
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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: 8
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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: 30
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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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+ | 3.5358 | 1.0 | 500 | 1.5944 | 1.0201 |
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+ | 0.8368 | 2.01 | 1000 | 0.5641 | 0.5463 |
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+ | 0.4255 | 3.01 | 1500 | 0.4739 | 0.4685 |
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+ | 0.304 | 4.02 | 2000 | 0.4171 | 0.4308 |
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+ | 0.2395 | 5.02 | 2500 | 0.4240 | 0.4073 |
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+ | 0.1912 | 6.02 | 3000 | 0.4893 | 0.4047 |
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+ | 0.1645 | 7.03 | 3500 | 0.4746 | 0.3889 |
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+ | 0.1435 | 8.03 | 4000 | 0.4155 | 0.3854 |
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+ | 0.124 | 9.04 | 4500 | 0.4588 | 0.3723 |
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+ | 0.1088 | 10.04 | 5000 | 0.4506 | 0.3741 |
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+ | 0.1016 | 11.04 | 5500 | 0.4440 | 0.3697 |
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+ | 0.085 | 12.05 | 6000 | 0.4652 | 0.3705 |
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+ | 0.0814 | 13.05 | 6500 | 0.5103 | 0.3631 |
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+ | 0.075 | 14.06 | 7000 | 0.4837 | 0.3626 |
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+ | 0.069 | 15.06 | 7500 | 0.4987 | 0.3614 |
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+ | 0.058 | 16.06 | 8000 | 0.4940 | 0.3554 |
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+ | 0.0556 | 17.07 | 8500 | 0.5129 | 0.3582 |
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+ | 0.0528 | 18.07 | 9000 | 0.5216 | 0.3616 |
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+ | 0.0458 | 19.08 | 9500 | 0.5110 | 0.3521 |
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+ | 0.0446 | 20.08 | 10000 | 0.5013 | 0.3539 |
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+ | 0.0411 | 21.08 | 10500 | 0.5126 | 0.3457 |
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+ | 0.0361 | 22.09 | 11000 | 0.5372 | 0.3403 |
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+ | 0.0326 | 23.09 | 11500 | 0.5216 | 0.3427 |
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+ | 0.0313 | 24.1 | 12000 | 0.5583 | 0.3426 |
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+ | 0.0281 | 25.1 | 12500 | 0.5330 | 0.3422 |
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+ | 0.0239 | 26.1 | 13000 | 0.5325 | 0.3377 |
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+ | 0.0246 | 27.11 | 13500 | 0.5414 | 0.3369 |
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+ | 0.0229 | 28.11 | 14000 | 0.5176 | 0.3345 |
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+ | 0.0227 | 29.12 | 14500 | 0.5237 | 0.3346 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.17.0
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+ - Pytorch 1.11.0+cu113
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+ - Datasets 1.18.3
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+ - Tokenizers 0.12.1