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--- |
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license: apache-2.0 |
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tags: |
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- audio-classification |
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- generated_from_trainer |
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datasets: |
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- mir_st500 |
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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec2-base-mirst500 |
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results: [] |
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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-mirst500 |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the /workspace/datasets/datasets/MIR_ST500/MIR_ST500_AUDIO_CLASSIFICATION.py dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1219 |
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- Accuracy: 0.5817 |
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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: 16 |
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- eval_batch_size: 1 |
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- seed: 0 |
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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 2 |
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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: 1.0 |
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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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| 1.1779 | 1.0 | 1304 | 1.1219 | 0.5817 | |
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### Framework versions |
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- Transformers 4.15.0 |
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- Pytorch 1.9.1+cu102 |
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- Datasets 2.0.0 |
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- Tokenizers 0.10.3 |
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