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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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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: wav2vec2-base-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: 0.8 |
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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-finetuned-gtzan |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7670 |
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- Accuracy: 0.8 |
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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: 3e-05 |
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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: 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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| 2.0554 | 1.0 | 100 | 2.0109 | 0.465 | |
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| 1.5036 | 2.0 | 200 | 1.5547 | 0.53 | |
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| 1.348 | 3.0 | 300 | 1.2558 | 0.685 | |
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| 1.1877 | 4.0 | 400 | 1.1226 | 0.7 | |
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| 0.8857 | 5.0 | 500 | 0.9978 | 0.76 | |
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| 0.6167 | 6.0 | 600 | 0.9513 | 0.755 | |
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| 0.5439 | 7.0 | 700 | 0.8185 | 0.78 | |
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| 0.5015 | 8.0 | 800 | 0.7880 | 0.815 | |
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| 0.2221 | 9.0 | 900 | 0.7777 | 0.8 | |
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| 0.3112 | 10.0 | 1000 | 0.7670 | 0.8 | |
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### Framework versions |
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- Transformers 4.34.1 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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