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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: anton-l/wav2vec2-base-ft-keyword-spotting |
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tags: |
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- generated_from_trainer |
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datasets: |
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- minds14 |
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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec2-minds14-audio-classification-all |
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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: minds14 |
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type: minds14 |
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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: 0.09730722154222766 |
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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-minds14-audio-classification-all |
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This model is a fine-tuned version of [anton-l/wav2vec2-base-ft-keyword-spotting](https://huggingface.co/anton-l/wav2vec2-base-ft-keyword-spotting) on the minds14 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.6367 |
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- Accuracy: 0.0973 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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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| 2.6374 | 0.9951 | 51 | 2.6375 | 0.0894 | |
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| 2.6347 | 1.9902 | 102 | 2.6334 | 0.0900 | |
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| 2.6352 | 2.9854 | 153 | 2.6323 | 0.0930 | |
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| 2.6282 | 4.0 | 205 | 2.6280 | 0.0924 | |
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| 2.6224 | 4.9951 | 256 | 2.6398 | 0.0894 | |
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| 2.6122 | 5.9902 | 307 | 2.6306 | 0.0912 | |
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| 2.6225 | 6.9854 | 358 | 2.6325 | 0.0906 | |
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| 2.6196 | 8.0 | 410 | 2.6358 | 0.0961 | |
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| 2.6154 | 8.9951 | 461 | 2.6357 | 0.0924 | |
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| 2.6028 | 9.9512 | 510 | 2.6367 | 0.0973 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.19.1 |
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