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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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- audiofolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: my_custom2_model |
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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: audiofolder |
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type: audiofolder |
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config: default |
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split: train |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.9166666666666666 |
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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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# my_custom2_model |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4030 |
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- Accuracy: 0.9167 |
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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: 2 |
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- total_train_batch_size: 8 |
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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: 20 |
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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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| 0.1798 | 1.0 | 6 | 0.4439 | 0.75 | |
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| 0.2051 | 2.0 | 12 | 0.5505 | 0.5833 | |
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| 0.1612 | 3.0 | 18 | 0.1884 | 0.9167 | |
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| 0.2032 | 4.0 | 24 | 0.2759 | 0.9167 | |
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| 0.1803 | 5.0 | 30 | 0.5196 | 0.8333 | |
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| 0.0478 | 6.0 | 36 | 0.3214 | 0.9167 | |
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| 0.1159 | 7.0 | 42 | 0.3311 | 0.9167 | |
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| 0.031 | 8.0 | 48 | 0.6261 | 0.8333 | |
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| 0.0263 | 9.0 | 54 | 0.3536 | 0.9167 | |
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| 0.2505 | 10.0 | 60 | 0.3637 | 0.9167 | |
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| 0.018 | 11.0 | 66 | 0.3721 | 0.9167 | |
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| 0.0167 | 12.0 | 72 | 0.6487 | 0.8333 | |
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| 0.0154 | 13.0 | 78 | 0.7422 | 0.8333 | |
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| 0.0144 | 14.0 | 84 | 0.7221 | 0.8333 | |
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| 0.0129 | 15.0 | 90 | 0.5876 | 0.8333 | |
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| 0.0123 | 16.0 | 96 | 0.4041 | 0.9167 | |
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| 0.0118 | 17.0 | 102 | 0.4000 | 0.9167 | |
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| 0.0115 | 18.0 | 108 | 0.4015 | 0.9167 | |
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| 0.0112 | 19.0 | 114 | 0.4025 | 0.9167 | |
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| 0.011 | 20.0 | 120 | 0.4030 | 0.9167 | |
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### Framework versions |
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- Transformers 4.50.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.5.0 |
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- Tokenizers 0.21.1 |
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