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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: ctrlv-speechrecognition-model
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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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+ # ctrlv-speechrecognition-model
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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: 0.4730
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+ - Wer: 0.3031
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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: 32
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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: 60
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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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+ | 3.53 | 3.45 | 500 | 1.4021 | 0.9307 |
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+ | 0.6077 | 6.9 | 1000 | 0.4255 | 0.4353 |
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+ | 0.2331 | 10.34 | 1500 | 0.3887 | 0.3650 |
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+ | 0.1436 | 13.79 | 2000 | 0.3579 | 0.3393 |
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+ | 0.1021 | 17.24 | 2500 | 0.4447 | 0.3440 |
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+ | 0.0797 | 20.69 | 3000 | 0.4041 | 0.3291 |
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+ | 0.0657 | 24.14 | 3500 | 0.4262 | 0.3368 |
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+ | 0.0525 | 27.59 | 4000 | 0.4937 | 0.3429 |
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+ | 0.0454 | 31.03 | 4500 | 0.4449 | 0.3244 |
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+ | 0.0373 | 34.48 | 5000 | 0.4363 | 0.3288 |
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+ | 0.0321 | 37.93 | 5500 | 0.4519 | 0.3204 |
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+ | 0.0288 | 41.38 | 6000 | 0.4440 | 0.3145 |
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+ | 0.0259 | 44.83 | 6500 | 0.4691 | 0.3182 |
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+ | 0.0203 | 48.28 | 7000 | 0.5062 | 0.3162 |
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+ | 0.0171 | 51.72 | 7500 | 0.4762 | 0.3129 |
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+ | 0.0166 | 55.17 | 8000 | 0.4772 | 0.3090 |
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+ | 0.0147 | 58.62 | 8500 | 0.4730 | 0.3031 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.11.3
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+ - Pytorch 1.10.0+cu111
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+ - Datasets 1.18.3
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+ - Tokenizers 0.10.3