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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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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: hubert-base-ls960-finetuned-gtzan
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results:
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- task:
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name: Audio Classification
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type: audio-classification
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dataset:
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name: GTZAN
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type: marsyas/gtzan
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config: all
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split: train
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args: all
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.85
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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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# hubert-base-ls960-finetuned-gtzan
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This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5673
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- Accuracy: 0.85
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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: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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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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| 2.0215 | 1.0 | 112 | 1.9334 | 0.2 |
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| 1.5799 | 2.0 | 225 | 1.3860 | 0.58 |
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| 1.1392 | 3.0 | 337 | 1.2514 | 0.55 |
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| 0.9529 | 4.0 | 450 | 0.9821 | 0.65 |
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| 0.7872 | 5.0 | 562 | 0.8525 | 0.74 |
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| 0.7504 | 6.0 | 675 | 0.9070 | 0.71 |
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| 0.8104 | 7.0 | 787 | 0.5771 | 0.83 |
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| 0.303 | 8.0 | 900 | 0.6943 | 0.81 |
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| 0.3939 | 9.0 | 1012 | 0.6368 | 0.84 |
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| 0.6499 | 9.96 | 1120 | 0.5673 | 0.85 |
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### Framework versions
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- Transformers 4.31.0.dev0
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- Pytorch 1.13.0
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- Datasets 2.1.0
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- Tokenizers 0.13.3
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