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README.md
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---
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tags:
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- generated_from_trainer
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datasets:
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- audiofolder
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metrics:
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- accuracy
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model-index:
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- name: wav2vec2-base-random-stop-classification-3
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results: []
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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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# wav2vec2-base-random-stop-classification-3
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This model is a fine-tuned version of [](https://huggingface.co/) on the audiofolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3662
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- Accuracy: 0.8753
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 256
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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_ratio: 0.1
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- num_epochs: 25
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.6931 | 0.99 | 18 | 0.6542 | 0.6178 |
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| 0.6854 | 1.97 | 36 | 0.6173 | 0.6696 |
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| 0.6617 | 2.96 | 54 | 0.5338 | 0.7343 |
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| 0.6747 | 4.0 | 73 | 0.6521 | 0.6757 |
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| 0.5626 | 4.99 | 91 | 0.4320 | 0.8072 |
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| 0.5127 | 5.97 | 109 | 0.4987 | 0.7834 |
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| 0.486 | 6.96 | 127 | 0.3753 | 0.8467 |
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| 0.4393 | 8.0 | 146 | 0.4076 | 0.8290 |
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| 0.4191 | 8.99 | 164 | 0.3877 | 0.8454 |
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| 0.4287 | 9.97 | 182 | 0.3613 | 0.8549 |
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| 0.4161 | 10.96 | 200 | 0.3714 | 0.8556 |
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| 0.3938 | 12.0 | 219 | 0.3561 | 0.8569 |
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| 0.3736 | 12.99 | 237 | 0.3914 | 0.8583 |
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| 0.3571 | 13.97 | 255 | 0.3917 | 0.8535 |
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| 0.3711 | 14.96 | 273 | 0.4288 | 0.8222 |
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| 0.3303 | 16.0 | 292 | 0.3680 | 0.8638 |
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| 0.3355 | 16.99 | 310 | 0.3724 | 0.8631 |
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| 0.3523 | 17.97 | 328 | 0.3741 | 0.8644 |
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| 0.3384 | 18.96 | 346 | 0.3726 | 0.8597 |
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| 0.3063 | 20.0 | 365 | 0.3705 | 0.8658 |
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| 0.2984 | 20.99 | 383 | 0.3866 | 0.8604 |
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| 0.2841 | 21.97 | 401 | 0.3897 | 0.8590 |
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| 0.3057 | 22.96 | 419 | 0.3662 | 0.8699 |
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| 0.2831 | 24.0 | 438 | 0.3627 | 0.8760 |
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| 0.2863 | 24.66 | 450 | 0.3662 | 0.8753 |
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 1.13.0
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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