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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-4 |
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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-4 |
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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: 0.3843 |
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- Accuracy: 0.8706 |
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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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| 0.6928 | 0.99 | 18 | 0.6588 | 0.6267 | |
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| 0.6746 | 1.97 | 36 | 0.5702 | 0.6969 | |
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| 0.5823 | 2.96 | 54 | 0.5035 | 0.7772 | |
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| 0.5573 | 4.0 | 73 | 0.4111 | 0.8188 | |
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| 0.5324 | 4.99 | 91 | 0.4359 | 0.7997 | |
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| 0.6058 | 5.97 | 109 | 0.4688 | 0.7875 | |
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| 0.4805 | 6.96 | 127 | 0.4055 | 0.8351 | |
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| 0.4641 | 8.0 | 146 | 0.4024 | 0.8351 | |
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| 0.4292 | 8.99 | 164 | 0.3913 | 0.8474 | |
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| 0.4217 | 9.97 | 182 | 0.3975 | 0.8522 | |
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| 0.3892 | 10.96 | 200 | 0.3808 | 0.8460 | |
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| 0.4056 | 12.0 | 219 | 0.4126 | 0.8515 | |
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| 0.3848 | 12.99 | 237 | 0.3602 | 0.8508 | |
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| 0.3698 | 13.97 | 255 | 0.3913 | 0.8488 | |
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| 0.3893 | 14.96 | 273 | 0.3611 | 0.8692 | |
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| 0.3341 | 16.0 | 292 | 0.3791 | 0.8624 | |
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| 0.3376 | 16.99 | 310 | 0.3578 | 0.8624 | |
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| 0.3331 | 17.97 | 328 | 0.3660 | 0.8658 | |
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| 0.3215 | 18.96 | 346 | 0.3817 | 0.8535 | |
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| 0.2982 | 20.0 | 365 | 0.4000 | 0.8658 | |
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| 0.2885 | 20.99 | 383 | 0.3674 | 0.8658 | |
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| 0.3124 | 21.97 | 401 | 0.3770 | 0.8672 | |
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| 0.2926 | 22.96 | 419 | 0.3779 | 0.8651 | |
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| 0.2941 | 24.0 | 438 | 0.3775 | 0.8733 | |
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| 0.2699 | 24.66 | 450 | 0.3843 | 0.8706 | |
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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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