transformers pytorch whisper audio-classification generated_from_trainer base_model:parambharat/whisper-tiny-south-indic license:apache-2.0 endpoints_compatible region:us
---
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
