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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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datasets:
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- marsyas/gtzan
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metrics:
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- accuracy
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model-index:
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- name: whisper-large-v2-finetuned-gtzan
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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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# whisper-large-v2-finetuned-gtzan
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This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7142
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- Accuracy: 0.9
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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: 1
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- eval_batch_size: 1
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 2
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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: 10
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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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| 2.0464 | 1.0 | 449 | 1.6761 | 0.42 |
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| 0.9369 | 2.0 | 899 | 1.0398 | 0.74 |
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| 1.0591 | 3.0 | 1348 | 1.0710 | 0.78 |
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| 0.0632 | 4.0 | 1798 | 0.6605 | 0.86 |
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| 0.0022 | 5.0 | 2247 | 1.0940 | 0.82 |
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| 0.0004 | 6.0 | 2697 | 0.7089 | 0.92 |
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| 0.0004 | 7.0 | 3146 | 0.6176 | 0.92 |
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| 0.0005 | 8.0 | 3596 | 0.6688 | 0.9 |
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| 0.0002 | 9.0 | 4045 | 0.7052 | 0.9 |
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| 0.0002 | 9.99 | 4490 | 0.7142 | 0.9 |
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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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