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whisper-tiny-south-indic-audio-abuse-feature

Audio Classification
Transformers
PyTorch
whisper
Generated from Trainer
Inference Endpoints
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metadata
license: apache-2.0
base_model: parambharat/whisper-tiny-south-indic
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: whisper-tiny-south-indic-audio-abuse-feature
    results: []

whisper-tiny-south-indic-audio-abuse-feature

This model is a fine-tuned version of parambharat/whisper-tiny-south-indic on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.8754
  • Accuracy: 0.8091
  • Macro F1-score: 0.7326

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 1e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 12

Training results

Training Loss Epoch Step Validation Loss Accuracy Macro F1-score
7.6265 0.29 10 7.5999 0.0 0.0
7.5514 0.58 20 7.4739 0.0 0.0
7.3762 0.86 30 7.2108 0.7073 0.2762
7.0242 1.15 40 6.6877 0.7114 0.4157
6.421 1.44 50 6.0112 0.7114 0.4157
5.7786 1.73 60 5.4468 0.7114 0.4157
5.2429 2.01 70 4.9849 0.7114 0.4157
4.8449 2.3 80 4.5921 0.7114 0.4157
4.5013 2.59 90 4.2484 0.7114 0.4157
4.1317 2.88 100 3.9375 0.7114 0.4157
3.8904 3.17 110 3.6543 0.7114 0.4157
3.5933 3.45 120 3.3909 0.7114 0.4157
3.3129 3.74 130 3.1460 0.7114 0.4157
3.0954 4.03 140 2.9201 0.7114 0.4157
2.8817 4.32 150 2.7098 0.7114 0.4157
2.7003 4.6 160 2.5173 0.7114 0.4157
2.5074 4.89 170 2.3380 0.7114 0.4157
2.3684 5.18 180 2.1744 0.7114 0.4157
2.1876 5.47 190 2.0227 0.7114 0.4157
2.0526 5.76 200 1.8856 0.7114 0.4157
1.8551 6.04 210 1.7647 0.7114 0.4157
1.7855 6.33 220 1.6472 0.7114 0.4157
1.7239 6.62 230 1.5505 0.7358 0.4996
1.5197 6.91 240 1.4623 0.7114 0.4157
1.485 7.19 250 1.3723 0.7439 0.5250
1.4318 7.48 260 1.2978 0.7642 0.5914
1.3828 7.77 270 1.2308 0.7805 0.6390
1.1559 8.06 280 1.1848 0.7398 0.5124
1.1692 8.35 290 1.1189 0.7886 0.6581
1.2058 8.63 300 1.0709 0.7846 0.6486
1.1676 8.92 310 1.0313 0.7886 0.6635
1.0257 9.21 320 0.9966 0.7886 0.6581
0.9943 9.5 330 0.9652 0.7886 0.6635
0.9894 9.78 340 0.9398 0.7927 0.6726
1.0581 10.07 350 0.9206 0.8171 0.7313
0.9395 10.36 360 0.9003 0.8008 0.6992
0.9766 10.65 370 0.8873 0.7886 0.6687
0.9291 10.94 380 0.8759 0.8089 0.7155
0.8967 11.22 390 0.8704 0.7927 0.6726
0.9463 11.51 400 0.8656 0.7967 0.6862

Framework versions

  • Transformers 4.33.0
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.13.3