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--- |
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license: apache-2.0 |
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base_model: yuval6967/wav2vec2-base-finetuned-gtzan |
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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-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: 0.78 |
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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-finetuned-gtzan |
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This model is a fine-tuned version of [yuval6967/wav2vec2-base-finetuned-gtzan](https://huggingface.co/yuval6967/wav2vec2-base-finetuned-gtzan) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3065 |
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- Accuracy: 0.78 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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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- mixed_precision_training: Native AMP |
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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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| 0.6708 | 0.9956 | 112 | 1.2056 | 0.75 | |
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| 0.6752 | 2.0 | 225 | 1.1245 | 0.78 | |
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| 0.1894 | 2.9956 | 337 | 1.0640 | 0.81 | |
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| 0.2192 | 4.0 | 450 | 1.3034 | 0.76 | |
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| 0.2675 | 4.9956 | 562 | 1.0633 | 0.81 | |
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| 0.1237 | 6.0 | 675 | 1.3065 | 0.78 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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