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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-1 |
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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-1 |
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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: 0.4066 |
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- Accuracy: 0.8651 |
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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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| 0.6949 | 0.99 | 18 | 0.6706 | 0.5906 | |
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| 0.6753 | 1.97 | 36 | 0.6470 | 0.6383 | |
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| 0.6231 | 2.96 | 54 | 0.5590 | 0.7302 | |
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| 0.544 | 4.0 | 73 | 0.4623 | 0.7977 | |
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| 0.4806 | 4.99 | 91 | 0.4061 | 0.8317 | |
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| 0.4543 | 5.97 | 109 | 0.5891 | 0.7643 | |
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| 0.4947 | 6.96 | 127 | 0.3944 | 0.8386 | |
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| 0.4431 | 8.0 | 146 | 0.4528 | 0.8093 | |
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| 0.4147 | 8.99 | 164 | 0.4560 | 0.8222 | |
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| 0.4094 | 9.97 | 182 | 0.4193 | 0.8447 | |
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| 0.3906 | 10.96 | 200 | 0.3846 | 0.8549 | |
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| 0.3835 | 12.0 | 219 | 0.3845 | 0.8569 | |
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| 0.3632 | 12.99 | 237 | 0.3660 | 0.8644 | |
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| 0.3622 | 13.97 | 255 | 0.4107 | 0.8617 | |
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| 0.3472 | 14.96 | 273 | 0.3733 | 0.8685 | |
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| 0.3419 | 16.0 | 292 | 0.4496 | 0.8467 | |
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| 0.3074 | 16.99 | 310 | 0.3987 | 0.8638 | |
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| 0.3278 | 17.97 | 328 | 0.3740 | 0.8665 | |
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| 0.2841 | 18.96 | 346 | 0.3999 | 0.8651 | |
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| 0.2837 | 20.0 | 365 | 0.3954 | 0.8604 | |
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| 0.2928 | 20.99 | 383 | 0.3871 | 0.8644 | |
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| 0.3002 | 21.97 | 401 | 0.4978 | 0.8386 | |
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| 0.2783 | 22.96 | 419 | 0.4079 | 0.8692 | |
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| 0.2703 | 24.0 | 438 | 0.3977 | 0.8713 | |
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| 0.2816 | 24.66 | 450 | 0.4066 | 0.8651 | |
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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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