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wav2vec2-ljspeech-gruut

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
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wav2vec2
phoneme-recognition
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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+ metrics:
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+ - wer
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+ model-index:
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+ - name: wav2vec2-ljspeech-gruut
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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-ljspeech-gruut
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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: 0.0683
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+ - Wer: 0.0099
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+ - Cer: 0.0058
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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: 16
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 32
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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: 30.0
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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 | Cer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
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+ | No log | 1.0 | 348 | 2.2818 | 1.0 | 1.0 |
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+ | 2.6692 | 2.0 | 696 | 0.2045 | 0.0527 | 0.0299 |
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+ | 0.2225 | 3.0 | 1044 | 0.1162 | 0.0319 | 0.0189 |
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+ | 0.2225 | 4.0 | 1392 | 0.0927 | 0.0235 | 0.0147 |
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+ | 0.0868 | 5.0 | 1740 | 0.0797 | 0.0218 | 0.0143 |
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+ | 0.0598 | 6.0 | 2088 | 0.0715 | 0.0197 | 0.0128 |
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+ | 0.0598 | 7.0 | 2436 | 0.0652 | 0.0160 | 0.0103 |
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+ | 0.0447 | 8.0 | 2784 | 0.0571 | 0.0152 | 0.0095 |
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+ | 0.0368 | 9.0 | 3132 | 0.0608 | 0.0163 | 0.0112 |
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+ | 0.0368 | 10.0 | 3480 | 0.0586 | 0.0137 | 0.0083 |
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+ | 0.0303 | 11.0 | 3828 | 0.0641 | 0.0141 | 0.0085 |
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+ | 0.0273 | 12.0 | 4176 | 0.0656 | 0.0131 | 0.0079 |
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+ | 0.0232 | 13.0 | 4524 | 0.0690 | 0.0133 | 0.0082 |
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+ | 0.0232 | 14.0 | 4872 | 0.0598 | 0.0128 | 0.0079 |
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+ | 0.0189 | 15.0 | 5220 | 0.0671 | 0.0121 | 0.0074 |
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+ | 0.017 | 16.0 | 5568 | 0.0654 | 0.0114 | 0.0069 |
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+ | 0.017 | 17.0 | 5916 | 0.0751 | 0.0118 | 0.0073 |
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+ | 0.0146 | 18.0 | 6264 | 0.0653 | 0.0112 | 0.0068 |
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+ | 0.0127 | 19.0 | 6612 | 0.0682 | 0.0112 | 0.0069 |
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+ | 0.0127 | 20.0 | 6960 | 0.0678 | 0.0114 | 0.0068 |
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+ | 0.0114 | 21.0 | 7308 | 0.0656 | 0.0111 | 0.0066 |
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+ | 0.0101 | 22.0 | 7656 | 0.0669 | 0.0109 | 0.0066 |
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+ | 0.0092 | 23.0 | 8004 | 0.0677 | 0.0108 | 0.0065 |
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+ | 0.0092 | 24.0 | 8352 | 0.0653 | 0.0104 | 0.0063 |
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+ | 0.0088 | 25.0 | 8700 | 0.0673 | 0.0102 | 0.0063 |
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+ | 0.0074 | 26.0 | 9048 | 0.0669 | 0.0105 | 0.0064 |
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+ | 0.0074 | 27.0 | 9396 | 0.0707 | 0.0101 | 0.0061 |
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+ | 0.0066 | 28.0 | 9744 | 0.0673 | 0.0100 | 0.0060 |
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+ | 0.0058 | 29.0 | 10092 | 0.0689 | 0.0100 | 0.0059 |
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+ | 0.0058 | 30.0 | 10440 | 0.0683 | 0.0099 | 0.0058 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.26.0.dev0
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+ - Pytorch 1.10.0
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+ - Datasets 2.7.1
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+ - Tokenizers 0.13.2