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callmesan
/
whisper-audio-abuse-feature

Audio Classification
Transformers
PyTorch
whisper
Generated from Trainer
Inference Endpoints
Model card Files Community
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  1. README.md +101 -0
  2. config.json +2516 -0
  3. preprocessor_config.json +14 -0
  4. pytorch_model.bin +3 -0
  5. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: parambharat/whisper-tiny-south-indic
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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: whisper-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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+ # whisper-audio-abuse-feature
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+
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+ This model is a fine-tuned version of [parambharat/whisper-tiny-south-indic](https://huggingface.co/parambharat/whisper-tiny-south-indic) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4947
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+ - Accuracy: 0.8174
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+ - Macro F1-score: 0.7845
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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: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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: 20
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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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+ | 7.8152 | 0.52 | 10 | 7.7606 | 0.0 | 0.0 |
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+ | 7.6445 | 1.04 | 20 | 7.4368 | 0.6718 | 0.1348 |
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+ | 7.1349 | 1.56 | 30 | 6.6932 | 0.6897 | 0.4082 |
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+ | 6.2832 | 2.08 | 40 | 5.7185 | 0.6897 | 0.4082 |
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+ | 5.3726 | 2.6 | 50 | 4.8531 | 0.6897 | 0.4082 |
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+ | 4.4541 | 3.12 | 60 | 4.1519 | 0.6897 | 0.4082 |
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+ | 3.9045 | 3.64 | 70 | 3.5417 | 0.6897 | 0.4082 |
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+ | 3.3278 | 4.16 | 80 | 2.9984 | 0.6897 | 0.4082 |
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+ | 2.7361 | 4.68 | 90 | 2.5167 | 0.6897 | 0.4082 |
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+ | 2.3838 | 5.19 | 100 | 2.1039 | 0.6897 | 0.4082 |
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+ | 1.9557 | 5.71 | 110 | 1.7366 | 0.6897 | 0.4082 |
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+ | 1.5922 | 6.23 | 120 | 1.4170 | 0.6897 | 0.4082 |
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+ | 1.3228 | 6.75 | 130 | 1.1497 | 0.7068 | 0.4669 |
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+ | 1.0767 | 7.27 | 140 | 0.9322 | 0.7779 | 0.6610 |
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+ | 0.8649 | 7.79 | 150 | 0.7814 | 0.7860 | 0.6800 |
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+ | 0.7058 | 8.31 | 160 | 0.6608 | 0.8165 | 0.7453 |
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+ | 0.6253 | 8.83 | 170 | 0.5688 | 0.8327 | 0.7936 |
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+ | 0.5269 | 9.35 | 180 | 0.5137 | 0.8291 | 0.7896 |
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+ | 0.5016 | 9.87 | 190 | 0.4862 | 0.8300 | 0.7747 |
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+ | 0.4409 | 10.39 | 200 | 0.4776 | 0.8040 | 0.7796 |
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+ | 0.3793 | 10.91 | 210 | 0.4511 | 0.8345 | 0.8048 |
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+ | 0.3501 | 11.43 | 220 | 0.4491 | 0.8228 | 0.7922 |
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+ | 0.3692 | 11.95 | 230 | 0.4254 | 0.8327 | 0.7982 |
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+ | 0.3148 | 12.47 | 240 | 0.4452 | 0.8228 | 0.7901 |
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+ | 0.3114 | 12.99 | 250 | 0.4543 | 0.8345 | 0.7905 |
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+ | 0.2812 | 13.51 | 260 | 0.4398 | 0.8363 | 0.7992 |
82
+ | 0.2635 | 14.03 | 270 | 0.4607 | 0.8327 | 0.7960 |
83
+ | 0.2491 | 14.55 | 280 | 0.4818 | 0.8327 | 0.7864 |
84
+ | 0.2825 | 15.06 | 290 | 0.4616 | 0.8219 | 0.7920 |
85
+ | 0.2494 | 15.58 | 300 | 0.4784 | 0.8129 | 0.7897 |
86
+ | 0.2127 | 16.1 | 310 | 0.4669 | 0.8273 | 0.7862 |
87
+ | 0.2003 | 16.62 | 320 | 0.4760 | 0.8174 | 0.7796 |
88
+ | 0.1907 | 17.14 | 330 | 0.4845 | 0.8246 | 0.7943 |
89
+ | 0.177 | 17.66 | 340 | 0.4870 | 0.8219 | 0.7867 |
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+ | 0.1877 | 18.18 | 350 | 0.4884 | 0.8201 | 0.7909 |
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+ | 0.1511 | 18.7 | 360 | 0.4907 | 0.8228 | 0.7845 |
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+ | 0.1826 | 19.22 | 370 | 0.4932 | 0.8165 | 0.7839 |
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+ | 0.1419 | 19.74 | 380 | 0.4947 | 0.8174 | 0.7845 |
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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
99
+ - Pytorch 2.0.0
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+ - Datasets 2.1.0
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+ - Tokenizers 0.13.3
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+ ],
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