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--- |
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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: wav2vec2-base-random-stop-classification-3 |
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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-random-stop-classification-3 |
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This model is a fine-tuned version of [](https://huggingface.co/) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3662 |
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- Accuracy: 0.8753 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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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: 25 |
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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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| 0.6931 | 0.99 | 18 | 0.6542 | 0.6178 | |
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| 0.6854 | 1.97 | 36 | 0.6173 | 0.6696 | |
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| 0.6617 | 2.96 | 54 | 0.5338 | 0.7343 | |
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| 0.6747 | 4.0 | 73 | 0.6521 | 0.6757 | |
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| 0.5626 | 4.99 | 91 | 0.4320 | 0.8072 | |
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| 0.5127 | 5.97 | 109 | 0.4987 | 0.7834 | |
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| 0.486 | 6.96 | 127 | 0.3753 | 0.8467 | |
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| 0.4393 | 8.0 | 146 | 0.4076 | 0.8290 | |
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| 0.4191 | 8.99 | 164 | 0.3877 | 0.8454 | |
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| 0.4287 | 9.97 | 182 | 0.3613 | 0.8549 | |
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| 0.4161 | 10.96 | 200 | 0.3714 | 0.8556 | |
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| 0.3938 | 12.0 | 219 | 0.3561 | 0.8569 | |
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| 0.3736 | 12.99 | 237 | 0.3914 | 0.8583 | |
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| 0.3571 | 13.97 | 255 | 0.3917 | 0.8535 | |
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| 0.3711 | 14.96 | 273 | 0.4288 | 0.8222 | |
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| 0.3303 | 16.0 | 292 | 0.3680 | 0.8638 | |
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| 0.3355 | 16.99 | 310 | 0.3724 | 0.8631 | |
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| 0.3523 | 17.97 | 328 | 0.3741 | 0.8644 | |
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| 0.3384 | 18.96 | 346 | 0.3726 | 0.8597 | |
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| 0.3063 | 20.0 | 365 | 0.3705 | 0.8658 | |
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| 0.2984 | 20.99 | 383 | 0.3866 | 0.8604 | |
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| 0.2841 | 21.97 | 401 | 0.3897 | 0.8590 | |
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| 0.3057 | 22.96 | 419 | 0.3662 | 0.8699 | |
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| 0.2831 | 24.0 | 438 | 0.3627 | 0.8760 | |
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| 0.2863 | 24.66 | 450 | 0.3662 | 0.8753 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 1.13.0 |
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- Datasets 2.7.1 |
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- Tokenizers 0.13.2 |
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