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---
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: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# whisper-tiny-south-indic-audio-abuse-feature
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.
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
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