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README.md
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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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- accuracy
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model-index:
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- name: wav2vec2-base_music_speech_both_classification
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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_music_speech_both_classification
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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: 0.0586
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- Accuracy: 0.9847
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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: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 16
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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: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 8
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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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| 0.9458 | 1.0 | 66 | 0.8468 | 0.7405 |
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| 0.3785 | 2.0 | 132 | 0.2951 | 0.9771 |
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| 0.1762 | 3.0 | 198 | 0.2639 | 0.9313 |
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| 0.134 | 4.0 | 264 | 0.1084 | 0.9771 |
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| 0.0782 | 5.0 | 330 | 0.0877 | 0.9771 |
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| 0.0568 | 6.0 | 396 | 0.0912 | 0.9771 |
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| 0.0122 | 7.0 | 462 | 0.4056 | 0.9198 |
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| 0.059 | 8.0 | 528 | 0.0586 | 0.9847 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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