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--- |
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license: apache-2.0 |
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base_model: saketag73/classification_facebook_wav2vec2-base-finetuned-gtzan-2 |
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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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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.805 |
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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 [saketag73/classification_facebook_wav2vec2-base-finetuned-gtzan-2](https://huggingface.co/saketag73/classification_facebook_wav2vec2-base-finetuned-gtzan-2) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7271 |
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- Accuracy: 0.805 |
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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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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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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- 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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| 1.0116 | 1.0 | 25 | 1.0805 | 0.715 | |
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| 0.7603 | 2.0 | 50 | 1.0321 | 0.76 | |
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| 0.6462 | 3.0 | 75 | 0.8840 | 0.775 | |
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| 0.5343 | 4.0 | 100 | 0.8303 | 0.78 | |
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| 0.4705 | 5.0 | 125 | 0.9837 | 0.72 | |
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| 0.3806 | 6.0 | 150 | 0.8099 | 0.79 | |
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| 0.3126 | 7.0 | 175 | 0.7897 | 0.79 | |
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| 0.2727 | 8.0 | 200 | 0.6896 | 0.81 | |
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| 0.2301 | 9.0 | 225 | 0.7518 | 0.81 | |
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| 0.2138 | 10.0 | 250 | 0.7271 | 0.805 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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