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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base-960h |
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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-960h-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: 0.73 |
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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-960h-finetuned-gtzan |
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the GTZAN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0690 |
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- Accuracy: 0.73 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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: 15 |
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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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| 2.3011 | 0.9956 | 56 | 2.2915 | 0.1 | |
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| 2.2365 | 1.9911 | 112 | 2.1198 | 0.37 | |
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| 1.9162 | 2.9867 | 168 | 1.9024 | 0.42 | |
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| 1.7154 | 4.0 | 225 | 1.7397 | 0.39 | |
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| 1.757 | 4.9956 | 281 | 1.5732 | 0.47 | |
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| 1.546 | 5.9911 | 337 | 1.5172 | 0.47 | |
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| 1.5738 | 6.9867 | 393 | 1.3950 | 0.54 | |
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| 1.2893 | 8.0 | 450 | 1.4202 | 0.56 | |
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| 1.2745 | 8.9956 | 506 | 1.2819 | 0.59 | |
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| 1.2632 | 9.9911 | 562 | 1.2788 | 0.66 | |
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| 1.2195 | 10.9867 | 618 | 1.1909 | 0.63 | |
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| 1.1151 | 12.0 | 675 | 1.1605 | 0.62 | |
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| 1.0165 | 12.9956 | 731 | 1.1202 | 0.67 | |
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| 0.9418 | 13.9911 | 787 | 1.0747 | 0.73 | |
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| 0.9686 | 14.9333 | 840 | 1.0690 | 0.73 | |
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### Framework versions |
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- Transformers 4.43.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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