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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-2 |
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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-2 |
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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: 0.4265 |
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- Accuracy: 0.8569 |
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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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| 0.6925 | 0.99 | 18 | 0.6506 | 0.6049 | |
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| 0.6667 | 1.97 | 36 | 0.6474 | 0.6396 | |
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| 0.5762 | 2.96 | 54 | 0.5791 | 0.7670 | |
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| 0.559 | 4.0 | 73 | 0.4603 | 0.7963 | |
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| 0.4892 | 4.99 | 91 | 0.4248 | 0.8161 | |
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| 0.4853 | 5.97 | 109 | 0.4544 | 0.8113 | |
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| 0.4452 | 6.96 | 127 | 0.5181 | 0.8011 | |
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| 0.4747 | 8.0 | 146 | 0.3739 | 0.8454 | |
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| 0.4026 | 8.99 | 164 | 0.4483 | 0.8249 | |
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| 0.4326 | 9.97 | 182 | 0.3992 | 0.8447 | |
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| 0.4149 | 10.96 | 200 | 0.3607 | 0.8542 | |
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| 0.3995 | 12.0 | 219 | 0.4662 | 0.8256 | |
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| 0.36 | 12.99 | 237 | 0.4375 | 0.8495 | |
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| 0.3807 | 13.97 | 255 | 0.4013 | 0.8351 | |
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| 0.401 | 14.96 | 273 | 0.4875 | 0.8311 | |
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| 0.3349 | 16.0 | 292 | 0.3810 | 0.8610 | |
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| 0.3279 | 16.99 | 310 | 0.4288 | 0.8392 | |
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| 0.3111 | 17.97 | 328 | 0.4160 | 0.8460 | |
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| 0.3092 | 18.96 | 346 | 0.4469 | 0.8379 | |
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| 0.3202 | 20.0 | 365 | 0.4294 | 0.8563 | |
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| 0.3027 | 20.99 | 383 | 0.3928 | 0.8569 | |
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| 0.3022 | 21.97 | 401 | 0.4829 | 0.8399 | |
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| 0.2934 | 22.96 | 419 | 0.3978 | 0.8604 | |
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| 0.2789 | 24.0 | 438 | 0.4027 | 0.8610 | |
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| 0.2714 | 24.66 | 450 | 0.4265 | 0.8569 | |
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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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