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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: imrajeshkr/distilhubert-finetuned-speech_commands |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: distilhubert-finetuned-speech_commands-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: audiofolder |
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type: audiofolder |
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config: default |
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split: test |
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args: default |
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metrics: |
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- name: Precision |
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type: precision |
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value: 0.9759184555734861 |
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- name: Recall |
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type: recall |
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value: 0.9749126053876208 |
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- name: F1 |
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type: f1 |
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value: 0.9749296122020006 |
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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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# distilhubert-finetuned-speech_commands-finetuned-gtzan |
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This model is a fine-tuned version of [imrajeshkr/distilhubert-finetuned-speech_commands](https://huggingface.co/imrajeshkr/distilhubert-finetuned-speech_commands) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0934 |
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- Precision: 0.9759 |
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- Recall: 0.9749 |
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- F1: 0.9749 |
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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: 5e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Use 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: 5 |
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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 | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:| |
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| 0.2713 | 1.0 | 1216 | 0.2523 | 0.9172 | 0.9267 | 0.9166 | |
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| 0.137 | 2.0 | 2432 | 0.1119 | 0.9685 | 0.9667 | 0.9664 | |
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| 0.0295 | 3.0 | 3648 | 0.0977 | 0.9726 | 0.9703 | 0.9701 | |
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| 0.0037 | 4.0 | 4864 | 0.0956 | 0.9743 | 0.9733 | 0.9732 | |
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| 0.052 | 5.0 | 6080 | 0.0934 | 0.9759 | 0.9749 | 0.9749 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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