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End of training
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README.md
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- generated_from_trainer
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datasets:
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- marsyas/gtzan
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model-index:
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- name: distilhubert-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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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size:
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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_ratio: 0.1
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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| 1.
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| 0.862 | 3.0 | 225 | 0.7765 |
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| 0.6679 | 4.0 | 300 | 0.6600 |
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| 0.4188 | 5.0 | 375 | 0.4797 |
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| 0.3369 | 6.0 | 450 | 0.5607 |
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| 0.1591 | 7.0 | 525 | 0.4668 |
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| 0.0591 | 8.0 | 600 | 0.4493 |
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| 0.0718 | 9.0 | 675 | 0.4454 |
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### Framework versions
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- Transformers 4.32.1
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- Pytorch
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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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: distilhubert-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: 0.66
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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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This model is a fine-tuned version of [ntu-spml/distilhubert](https://huggingface.co/ntu-spml/distilhubert) on the GTZAN dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0372
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- Accuracy: 0.66
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.00011651033424866663
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- train_batch_size: 8
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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_ratio: 0.1
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- num_epochs: 2
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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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| 1.6048 | 1.0 | 113 | 1.2967 | 0.6 |
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| 1.0543 | 2.0 | 226 | 1.0372 | 0.66 |
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### Framework versions
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- Transformers 4.32.1
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- Pytorch 1.13.1
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- Datasets 2.14.4
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- Tokenizers 0.13.3
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