update model card README.md
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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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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: 0.85
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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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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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## Model description
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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:
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- eval_batch_size:
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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: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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| 1.9852 | 1.0 | 113 | 1.8289 | 0.34 |
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| 1.3305 | 2.0 | 226 | 1.2247 | 0.62 |
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| 1.0181 | 3.0 | 339 | 0.9353 | 0.77 |
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| 0.728 | 4.0 | 452 | 0.9143 | 0.74 |
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| 0.5623 | 5.0 | 565 | 0.6578 | 0.82 |
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| 0.3524 | 6.0 | 678 | 0.6504 | 0.82 |
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| 0.4248 | 7.0 | 791 | 0.5781 | 0.82 |
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| 0.1001 | 8.0 | 904 | 0.4987 | 0.88 |
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| 0.1922 | 9.0 | 1017 | 0.5163 | 0.85 |
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| 0.134 | 10.0 | 1130 | 0.5535 | 0.85 |
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### Framework versions
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- Transformers 4.31.0.dev0
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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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- eval_loss: 1.9915
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- eval_accuracy: 0.31
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- eval_runtime: 8.0771
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- eval_samples_per_second: 12.381
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- eval_steps_per_second: 0.867
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- epoch: 1.0
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- step: 57
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## Model description
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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: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 10
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### Framework versions
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- Transformers 4.31.0.dev0
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