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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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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.76 |
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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: 1.1430 |
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- Accuracy: 0.76 |
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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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- 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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| 2.2574 | 1.0 | 25 | 2.1793 | 0.445 | |
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| 1.9361 | 2.0 | 50 | 1.8937 | 0.475 | |
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| 1.7211 | 3.0 | 75 | 1.7034 | 0.54 | |
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| 1.5003 | 4.0 | 100 | 1.5038 | 0.63 | |
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| 1.3653 | 5.0 | 125 | 1.3770 | 0.7 | |
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| 1.2614 | 6.0 | 150 | 1.3169 | 0.69 | |
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| 1.1654 | 7.0 | 175 | 1.2444 | 0.725 | |
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| 1.0837 | 8.0 | 200 | 1.1828 | 0.755 | |
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| 1.0409 | 9.0 | 225 | 1.1549 | 0.755 | |
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| 1.0147 | 10.0 | 250 | 1.1430 | 0.76 | |
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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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