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update model card README.md

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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-5
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+ results: []
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+ ---
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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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+
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+ # wav2vec2-base-random-stop-classification-5
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+
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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: 0.4239
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+ - Accuracy: 0.8631
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.6916 | 0.99 | 18 | 0.6503 | 0.6362 |
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+ | 0.6628 | 1.97 | 36 | 0.5354 | 0.7391 |
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+ | 0.5922 | 2.96 | 54 | 0.4775 | 0.7786 |
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+ | 0.5158 | 4.0 | 73 | 0.4559 | 0.8072 |
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+ | 0.4733 | 4.99 | 91 | 0.4308 | 0.8188 |
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+ | 0.4935 | 5.97 | 109 | 0.5186 | 0.7888 |
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+ | 0.4512 | 6.96 | 127 | 0.4108 | 0.8358 |
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+ | 0.4397 | 8.0 | 146 | 0.4692 | 0.8270 |
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+ | 0.4037 | 8.99 | 164 | 0.4049 | 0.8304 |
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+ | 0.4053 | 9.97 | 182 | 0.4054 | 0.8379 |
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+ | 0.3774 | 10.96 | 200 | 0.4330 | 0.8379 |
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+ | 0.3624 | 12.0 | 219 | 0.3800 | 0.8495 |
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+ | 0.376 | 12.99 | 237 | 0.5123 | 0.8263 |
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+ | 0.3908 | 13.97 | 255 | 0.4049 | 0.8386 |
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+ | 0.3405 | 14.96 | 273 | 0.4200 | 0.8529 |
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+ | 0.3542 | 16.0 | 292 | 0.4040 | 0.8569 |
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+ | 0.3284 | 16.99 | 310 | 0.4578 | 0.8474 |
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+ | 0.3094 | 17.97 | 328 | 0.4465 | 0.8522 |
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+ | 0.2999 | 18.96 | 346 | 0.4126 | 0.8569 |
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+ | 0.3059 | 20.0 | 365 | 0.4139 | 0.8529 |
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+ | 0.2891 | 20.99 | 383 | 0.4101 | 0.8624 |
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+ | 0.2968 | 21.97 | 401 | 0.4589 | 0.8501 |
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+ | 0.2764 | 22.96 | 419 | 0.4263 | 0.8522 |
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+ | 0.2841 | 24.0 | 438 | 0.4350 | 0.8597 |
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+ | 0.2805 | 24.66 | 450 | 0.4239 | 0.8631 |
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+
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+
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+ ### Framework versions
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+
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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