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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: 0.88 |
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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: 0.5242 |
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- Accuracy: 0.88 |
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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: 1e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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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: 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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| 0.5894 | 1.0 | 56 | 0.6959 | 0.87 | |
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| 0.5636 | 1.99 | 112 | 0.7488 | 0.82 | |
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| 0.4387 | 2.99 | 168 | 0.7051 | 0.83 | |
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| 0.3296 | 4.0 | 225 | 0.6642 | 0.86 | |
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| 0.3094 | 5.0 | 281 | 0.6453 | 0.85 | |
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| 0.2881 | 5.99 | 337 | 0.6484 | 0.84 | |
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| 0.2712 | 6.99 | 393 | 0.5738 | 0.86 | |
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| 0.267 | 8.0 | 450 | 0.5593 | 0.86 | |
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| 0.1794 | 9.0 | 506 | 0.5699 | 0.86 | |
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| 0.2602 | 9.96 | 560 | 0.5242 | 0.88 | |
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### Framework versions |
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- Transformers 4.33.0 |
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- Pytorch 2.0.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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