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callmesan
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hindi_base_wav2vec2-audio-abuse-feature

Audio Classification
Transformers
PyTorch
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Community
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+ ---
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+ license: apache-2.0
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+ base_model: Harveenchadha/hindi_base_wav2vec2
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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: hindi_base_wav2vec2-audio-abuse-feature
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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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+ # hindi_base_wav2vec2-audio-abuse-feature
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+
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+ This model is a fine-tuned version of [Harveenchadha/hindi_base_wav2vec2](https://huggingface.co/Harveenchadha/hindi_base_wav2vec2) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7202
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+ - Accuracy: 0.6694
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+ - Macro F1-score: 0.6693
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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: 2e-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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1-score |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------------:|
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+ | 6.6553 | 0.77 | 10 | 6.6322 | 0.0 | 0.0 |
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+ | 6.5758 | 1.54 | 20 | 6.4417 | 0.5447 | 0.2151 |
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+ | 6.3599 | 2.31 | 30 | 6.1486 | 0.5122 | 0.3621 |
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+ | 6.0708 | 3.08 | 40 | 5.7751 | 0.5041 | 0.3351 |
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+ | 5.8361 | 3.85 | 50 | 5.4662 | 0.5041 | 0.3351 |
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+ | 5.5167 | 4.62 | 60 | 5.2127 | 0.5041 | 0.3351 |
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+ | 5.289 | 5.38 | 70 | 4.9640 | 0.5041 | 0.3351 |
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+ | 5.0266 | 6.15 | 80 | 4.7282 | 0.5041 | 0.3351 |
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+ | 4.78 | 6.92 | 90 | 4.5006 | 0.5041 | 0.3351 |
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+ | 4.6197 | 7.69 | 100 | 4.2787 | 0.5041 | 0.3351 |
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+ | 4.3798 | 8.46 | 110 | 4.0506 | 0.5041 | 0.3351 |
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+ | 4.2651 | 9.23 | 120 | 3.8315 | 0.5041 | 0.3351 |
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+ | 3.9832 | 10.0 | 130 | 3.6034 | 0.5041 | 0.3351 |
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+ | 3.7163 | 10.77 | 140 | 3.3782 | 0.5041 | 0.3351 |
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+ | 3.5481 | 11.54 | 150 | 3.1510 | 0.5041 | 0.3351 |
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+ | 3.305 | 12.31 | 160 | 2.9279 | 0.5041 | 0.3351 |
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+ | 3.1589 | 13.08 | 170 | 2.7102 | 0.5041 | 0.3351 |
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+ | 2.8368 | 13.85 | 180 | 2.4942 | 0.5041 | 0.3351 |
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+ | 2.5875 | 14.62 | 190 | 2.2896 | 0.5041 | 0.3351 |
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+ | 2.5938 | 15.38 | 200 | 2.0940 | 0.5041 | 0.3351 |
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+ | 2.2346 | 16.15 | 210 | 1.9083 | 0.5041 | 0.3351 |
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+ | 2.0404 | 16.92 | 220 | 1.7372 | 0.5041 | 0.3351 |
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+ | 1.8744 | 17.69 | 230 | 1.5755 | 0.5041 | 0.3351 |
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+ | 1.6581 | 18.46 | 240 | 1.4332 | 0.5041 | 0.3351 |
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+ | 1.7251 | 19.23 | 250 | 1.3152 | 0.5041 | 0.3351 |
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+ | 1.4569 | 20.0 | 260 | 1.2093 | 0.5041 | 0.3351 |
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+ | 1.3718 | 20.77 | 270 | 1.1160 | 0.5041 | 0.3351 |
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+ | 1.1743 | 21.54 | 280 | 1.0209 | 0.5041 | 0.3351 |
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+ | 1.0744 | 22.31 | 290 | 0.9585 | 0.6585 | 0.6309 |
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+ | 1.0933 | 23.08 | 300 | 0.8902 | 0.7019 | 0.6941 |
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+ | 0.9348 | 23.85 | 310 | 0.8504 | 0.6992 | 0.6940 |
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+ | 0.9611 | 24.62 | 320 | 0.8094 | 0.6911 | 0.6901 |
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+ | 0.8307 | 25.38 | 330 | 0.7750 | 0.6992 | 0.6992 |
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+ | 0.7863 | 26.15 | 340 | 0.7776 | 0.6802 | 0.6724 |
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+ | 0.7431 | 26.92 | 350 | 0.7624 | 0.6829 | 0.6737 |
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+ | 0.7607 | 27.69 | 360 | 0.7450 | 0.6775 | 0.6747 |
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+ | 0.8054 | 28.46 | 370 | 0.7161 | 0.6938 | 0.6914 |
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+ | 0.752 | 29.23 | 380 | 0.7021 | 0.6965 | 0.6946 |
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+ | 0.72 | 30.0 | 390 | 0.7060 | 0.6856 | 0.6846 |
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+ | 0.7252 | 30.77 | 400 | 0.6968 | 0.6911 | 0.6910 |
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+ | 0.6497 | 31.54 | 410 | 0.7016 | 0.6911 | 0.6905 |
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+ | 0.6215 | 32.31 | 420 | 0.7209 | 0.6856 | 0.6848 |
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+ | 0.6143 | 33.08 | 430 | 0.6941 | 0.6856 | 0.6856 |
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+ | 0.6778 | 33.85 | 440 | 0.6887 | 0.6856 | 0.6850 |
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+ | 0.6027 | 34.62 | 450 | 0.7010 | 0.6992 | 0.6990 |
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+ | 0.6644 | 35.38 | 460 | 0.7009 | 0.6721 | 0.6674 |
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+ | 0.6178 | 36.15 | 470 | 0.6840 | 0.7019 | 0.6985 |
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+ | 0.5817 | 36.92 | 480 | 0.6974 | 0.6829 | 0.6827 |
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+ | 0.5876 | 37.69 | 490 | 0.6914 | 0.6802 | 0.6801 |
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+ | 0.5474 | 38.46 | 500 | 0.7056 | 0.6856 | 0.6855 |
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+ | 0.5327 | 39.23 | 510 | 0.7128 | 0.6802 | 0.6800 |
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+ | 0.5648 | 40.0 | 520 | 0.7067 | 0.6748 | 0.6730 |
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+ | 0.6163 | 40.77 | 530 | 0.6804 | 0.6721 | 0.6721 |
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+ | 0.514 | 41.54 | 540 | 0.6965 | 0.6775 | 0.6774 |
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+ | 0.5817 | 42.31 | 550 | 0.7177 | 0.6775 | 0.6767 |
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+ | 0.5345 | 43.08 | 560 | 0.7136 | 0.6775 | 0.6772 |
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+ | 0.525 | 43.85 | 570 | 0.7159 | 0.6883 | 0.6876 |
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+ | 0.5043 | 44.62 | 580 | 0.7110 | 0.6802 | 0.6801 |
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+ | 0.5418 | 45.38 | 590 | 0.7149 | 0.6748 | 0.6746 |
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+ | 0.5129 | 46.15 | 600 | 0.7108 | 0.6694 | 0.6694 |
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+ | 0.5331 | 46.92 | 610 | 0.7118 | 0.6667 | 0.6667 |
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+ | 0.6061 | 47.69 | 620 | 0.7248 | 0.6802 | 0.6795 |
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+ | 0.5551 | 48.46 | 630 | 0.7196 | 0.6694 | 0.6694 |
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+ | 0.5049 | 49.23 | 640 | 0.7190 | 0.6640 | 0.6638 |
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+ | 0.4663 | 50.0 | 650 | 0.7202 | 0.6694 | 0.6693 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.0
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+ - Pytorch 2.0.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.13.3