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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base-960h |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: audioclass-alpha |
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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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# audioclass-alpha |
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0963 |
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- Accuracy: 0.9819 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 50 |
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- mixed_precision_training: Native AMP |
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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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| 3.3678 | 1.0 | 62 | 3.3612 | 0.0408 | |
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| 3.349 | 2.0 | 124 | 3.3402 | 0.0385 | |
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| 3.2935 | 3.0 | 186 | 3.2047 | 0.2494 | |
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| 2.9643 | 4.0 | 248 | 2.7250 | 0.5102 | |
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| 2.4158 | 5.0 | 310 | 2.1914 | 0.6621 | |
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| 1.9634 | 6.0 | 372 | 1.7440 | 0.7800 | |
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| 1.6144 | 7.0 | 434 | 1.3680 | 0.8503 | |
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| 1.2939 | 8.0 | 496 | 1.0948 | 0.8390 | |
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| 1.0933 | 9.0 | 558 | 0.8783 | 0.8776 | |
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| 0.8596 | 10.0 | 620 | 0.7053 | 0.9048 | |
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| 0.6664 | 11.0 | 682 | 0.6020 | 0.9184 | |
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| 0.5843 | 12.0 | 744 | 0.5392 | 0.9048 | |
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| 0.5714 | 13.0 | 806 | 0.4380 | 0.9297 | |
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| 0.4395 | 14.0 | 868 | 0.4434 | 0.9252 | |
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| 0.323 | 15.0 | 930 | 0.3000 | 0.9524 | |
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| 0.3218 | 16.0 | 992 | 0.2418 | 0.9546 | |
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| 0.3026 | 17.0 | 1054 | 0.2462 | 0.9524 | |
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| 0.2531 | 18.0 | 1116 | 0.2003 | 0.9660 | |
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| 0.2702 | 19.0 | 1178 | 0.1883 | 0.9637 | |
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| 0.2368 | 20.0 | 1240 | 0.1612 | 0.9728 | |
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| 0.2121 | 21.0 | 1302 | 0.1981 | 0.9637 | |
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| 0.2011 | 22.0 | 1364 | 0.1635 | 0.9683 | |
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| 0.1875 | 23.0 | 1426 | 0.1454 | 0.9728 | |
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| 0.1415 | 24.0 | 1488 | 0.1433 | 0.9683 | |
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| 0.1162 | 25.0 | 1550 | 0.1504 | 0.9660 | |
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| 0.0946 | 26.0 | 1612 | 0.1759 | 0.9615 | |
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| 0.1032 | 27.0 | 1674 | 0.1206 | 0.9751 | |
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| 0.095 | 28.0 | 1736 | 0.1123 | 0.9773 | |
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| 0.1526 | 29.0 | 1798 | 0.1267 | 0.9728 | |
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| 0.1003 | 30.0 | 1860 | 0.0953 | 0.9796 | |
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| 0.1371 | 31.0 | 1922 | 0.1158 | 0.9751 | |
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| 0.0765 | 32.0 | 1984 | 0.0963 | 0.9819 | |
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| 0.1152 | 33.0 | 2046 | 0.0929 | 0.9819 | |
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| 0.1344 | 34.0 | 2108 | 0.1103 | 0.9796 | |
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| 0.1067 | 35.0 | 2170 | 0.1065 | 0.9773 | |
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| 0.0847 | 36.0 | 2232 | 0.0898 | 0.9819 | |
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| 0.0835 | 37.0 | 2294 | 0.0934 | 0.9819 | |
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| 0.1009 | 38.0 | 2356 | 0.1136 | 0.9796 | |
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| 0.1272 | 39.0 | 2418 | 0.1315 | 0.9751 | |
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| 0.0463 | 40.0 | 2480 | 0.1127 | 0.9796 | |
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| 0.085 | 41.0 | 2542 | 0.0985 | 0.9796 | |
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| 0.0431 | 42.0 | 2604 | 0.0964 | 0.9773 | |
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| 0.0698 | 43.0 | 2666 | 0.1128 | 0.9773 | |
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| 0.0493 | 44.0 | 2728 | 0.0934 | 0.9796 | |
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| 0.1208 | 45.0 | 2790 | 0.0882 | 0.9819 | |
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| 0.0536 | 46.0 | 2852 | 0.0932 | 0.9796 | |
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| 0.064 | 47.0 | 2914 | 0.1008 | 0.9796 | |
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| 0.0538 | 48.0 | 2976 | 0.1094 | 0.9796 | |
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| 0.0774 | 49.0 | 3038 | 0.1081 | 0.9796 | |
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| 0.0379 | 50.0 | 3100 | 0.1085 | 0.9796 | |
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### Framework versions |
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- Transformers 4.36.0.dev0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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