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--- |
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library_name: transformers |
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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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- danavery/urbansound8K |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: wav2vec2-finetuned-urbansound8k |
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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: URBAN-SOUND8K |
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type: danavery/urbansound8K |
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args: audio-classification |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9650829994275901 |
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- name: F1 |
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type: f1 |
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value: 0.965058831730144 |
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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-finetuned-urbansound8k |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the URBAN-SOUND8K dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2672 |
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- Accuracy: 0.9651 |
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- F1: 0.9651 |
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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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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 8 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:| |
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| 0.6296 | 1.0 | 1747 | 0.9168 | 0.7098 | 0.6543 | |
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| 0.3658 | 2.0 | 3494 | 0.4589 | 0.8798 | 0.8788 | |
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| 0.108 | 3.0 | 5241 | 0.4362 | 0.9107 | 0.9102 | |
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| 0.3019 | 4.0 | 6988 | 0.4455 | 0.9216 | 0.9215 | |
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| 0.0019 | 5.0 | 8735 | 0.3645 | 0.9433 | 0.9433 | |
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| 0.0014 | 6.0 | 10482 | 0.3780 | 0.9416 | 0.9417 | |
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| 0.1803 | 7.0 | 12229 | 0.3196 | 0.9519 | 0.9519 | |
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| 0.0004 | 8.0 | 13976 | 0.2672 | 0.9651 | 0.9651 | |
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### Framework versions |
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- Transformers 4.52.4 |
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- Pytorch 2.7.1+cu126 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.1 |
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