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callmesan
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vakyansh-wav2vec2-odia-orm-100-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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+ base_model: Harveenchadha/vakyansh-wav2vec2-odia-orm-100
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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: vakyansh-wav2vec2-odia-orm-100-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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+ # vakyansh-wav2vec2-odia-orm-100-audio-abuse-feature
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+
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+ This model is a fine-tuned version of [Harveenchadha/vakyansh-wav2vec2-odia-orm-100](https://huggingface.co/Harveenchadha/vakyansh-wav2vec2-odia-orm-100) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7299
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+ - Accuracy: 0.7014
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+ - Macro F1-score: 0.6792
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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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+ | 6.7078 | 0.78 | 10 | 6.6948 | 0.0 | 0.0 |
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+ | 6.6539 | 1.57 | 20 | 6.5580 | 0.2 | 0.0342 |
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+ | 6.5111 | 2.35 | 30 | 6.3377 | 0.5726 | 0.3641 |
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+ | 6.268 | 3.14 | 40 | 6.0361 | 0.5726 | 0.3641 |
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+ | 6.0748 | 3.92 | 50 | 5.7417 | 0.5726 | 0.3641 |
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+ | 5.8205 | 4.71 | 60 | 5.4985 | 0.5726 | 0.3641 |
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+ | 5.6051 | 5.49 | 70 | 5.2743 | 0.5726 | 0.3641 |
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+ | 5.3589 | 6.27 | 80 | 5.0823 | 0.5726 | 0.3641 |
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+ | 5.2019 | 7.06 | 90 | 4.8953 | 0.5726 | 0.3641 |
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+ | 5.0528 | 7.84 | 100 | 4.7077 | 0.5726 | 0.3641 |
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+ | 4.868 | 8.63 | 110 | 4.5244 | 0.5726 | 0.3641 |
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+ | 4.7081 | 9.41 | 120 | 4.3347 | 0.5726 | 0.3641 |
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+ | 4.437 | 10.2 | 130 | 4.1455 | 0.5726 | 0.3641 |
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+ | 4.3225 | 10.98 | 140 | 3.9551 | 0.5726 | 0.3641 |
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+ | 4.0945 | 11.76 | 150 | 3.7694 | 0.5726 | 0.3641 |
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+ | 4.014 | 12.55 | 160 | 3.5710 | 0.5726 | 0.3641 |
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+ | 3.8491 | 13.33 | 170 | 3.3814 | 0.5726 | 0.3641 |
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+ | 3.4724 | 14.12 | 180 | 3.1873 | 0.5726 | 0.3641 |
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+ | 3.2728 | 14.9 | 190 | 2.9999 | 0.5726 | 0.3641 |
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+ | 3.1948 | 15.69 | 200 | 2.8224 | 0.5726 | 0.3641 |
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+ | 2.9968 | 16.47 | 210 | 2.6368 | 0.5726 | 0.3641 |
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+ | 2.6739 | 17.25 | 220 | 2.4462 | 0.5726 | 0.3641 |
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+ | 2.561 | 18.04 | 230 | 2.2871 | 0.5726 | 0.3641 |
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+ | 2.5101 | 18.82 | 240 | 2.1260 | 0.5726 | 0.3641 |
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+ | 2.3307 | 19.61 | 250 | 1.9620 | 0.5726 | 0.3641 |
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+ | 2.1022 | 20.39 | 260 | 1.8260 | 0.5726 | 0.3641 |
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+ | 1.9909 | 21.18 | 270 | 1.6933 | 0.5726 | 0.3641 |
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+ | 1.766 | 21.96 | 280 | 1.5644 | 0.5726 | 0.3641 |
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+ | 1.7143 | 22.75 | 290 | 1.4669 | 0.5726 | 0.3641 |
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+ | 1.5073 | 23.53 | 300 | 1.3482 | 0.5726 | 0.3641 |
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+ | 1.6055 | 24.31 | 310 | 1.2643 | 0.5726 | 0.3641 |
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+ | 1.321 | 25.1 | 320 | 1.1930 | 0.5726 | 0.3641 |
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+ | 1.2165 | 25.88 | 330 | 1.1128 | 0.5726 | 0.3641 |
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+ | 1.1484 | 26.67 | 340 | 1.0493 | 0.6712 | 0.6033 |
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+ | 1.1413 | 27.45 | 350 | 0.9925 | 0.7096 | 0.6737 |
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+ | 1.0462 | 28.24 | 360 | 0.9471 | 0.6877 | 0.6190 |
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+ | 0.9667 | 29.02 | 370 | 0.9209 | 0.7123 | 0.6869 |
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+ | 0.9918 | 29.8 | 380 | 0.8892 | 0.7205 | 0.6953 |
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+ | 0.9112 | 30.59 | 390 | 0.8414 | 0.7123 | 0.6705 |
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+ | 0.8666 | 31.37 | 400 | 0.8291 | 0.7123 | 0.6836 |
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+ | 0.8096 | 32.16 | 410 | 0.8284 | 0.6959 | 0.6501 |
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+ | 0.7987 | 32.94 | 420 | 0.7729 | 0.7425 | 0.7270 |
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+ | 0.7529 | 33.73 | 430 | 0.7542 | 0.7260 | 0.7023 |
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+ | 0.7605 | 34.51 | 440 | 0.7535 | 0.7260 | 0.7043 |
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+ | 0.7011 | 35.29 | 450 | 0.7882 | 0.6959 | 0.6891 |
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+ | 0.6868 | 36.08 | 460 | 0.7378 | 0.7260 | 0.7013 |
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+ | 0.6858 | 36.86 | 470 | 0.7518 | 0.7096 | 0.6865 |
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+ | 0.7546 | 37.65 | 480 | 0.7163 | 0.7342 | 0.7108 |
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+ | 0.6717 | 38.43 | 490 | 0.7158 | 0.7397 | 0.7158 |
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+ | 0.7048 | 39.22 | 500 | 0.7755 | 0.6575 | 0.6487 |
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+ | 0.6767 | 40.0 | 510 | 0.7469 | 0.7068 | 0.6798 |
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+ | 0.6621 | 40.78 | 520 | 0.7166 | 0.7205 | 0.7020 |
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+ | 0.6639 | 41.57 | 530 | 0.7143 | 0.7151 | 0.6934 |
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+ | 0.5988 | 42.35 | 540 | 0.7547 | 0.6767 | 0.6661 |
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+ | 0.6179 | 43.14 | 550 | 0.7394 | 0.7014 | 0.6820 |
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+ | 0.7033 | 43.92 | 560 | 0.7312 | 0.6986 | 0.6757 |
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+ | 0.6076 | 44.71 | 570 | 0.7331 | 0.6904 | 0.6674 |
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+ | 0.602 | 45.49 | 580 | 0.7341 | 0.6932 | 0.6718 |
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+ | 0.545 | 46.27 | 590 | 0.7363 | 0.6932 | 0.6738 |
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+ | 0.5881 | 47.06 | 600 | 0.7299 | 0.7014 | 0.6792 |
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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