---
library_name: transformers
language:
- te
base_model: kattojuprashanth238/whisper-small-te-v5
tags:
- generated_from_trainer
datasets:
- None
metrics:
- wer
model-index:
- name: Whisper Small Te - Prashanth Kattoju
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: HCU ASR Telugu Corpus
      type: None
      config: "te"
      split: None
    metrics:
    - name: Wer
      type: wer
      value: 15.932914046121594
---

<!-- 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 Small Te - Prashanth Kattoju

This model is a fine-tuned version of [kattojuprashanth238/whisper-small-te-v5](https://huggingface.co/kattojuprashanth238/whisper-small-te-v5) on the HCU ASR Telugu Corpus.
It achieves the following results on the evaluation set:
- Loss: 0.2009
- Wer Ortho: 51.4451
- Wer: 15.9329

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 1500

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
| 0.086         | 2.5063  | 50   | 0.1613          | 65.3179   | 19.2872 |
| 0.0096        | 5.0     | 100  | 0.1647          | 57.8035   | 17.8197 |
| 0.006         | 7.5063  | 150  | 0.1880          | 55.4913   | 14.6751 |
| 0.0032        | 10.0    | 200  | 0.1541          | 46.8208   | 12.3690 |
| 0.0027        | 12.5063 | 250  | 0.1631          | 48.5549   | 12.1593 |
| 0.0002        | 15.0    | 300  | 0.1617          | 44.5087   | 11.5304 |
| 0.0005        | 17.5063 | 350  | 0.1965          | 57.8035   | 14.6751 |
| 0.0034        | 20.0    | 400  | 0.1589          | 49.7110   | 12.9979 |
| 0.0036        | 22.5063 | 450  | 0.1761          | 49.7110   | 12.3690 |
| 0.0106        | 25.0    | 500  | 0.1630          | 62.4277   | 19.9161 |
| 0.005         | 27.5063 | 550  | 0.1809          | 54.3353   | 14.0461 |
| 0.0021        | 30.0    | 600  | 0.1801          | 52.6012   | 11.5304 |
| 0.0021        | 32.5063 | 650  | 0.1895          | 53.7572   | 14.4654 |
| 0.0027        | 35.0    | 700  | 0.1576          | 51.4451   | 13.6268 |
| 0.0033        | 37.5063 | 750  | 0.2080          | 58.9595   | 27.0440 |
| 0.0019        | 40.0    | 800  | 0.1958          | 49.7110   | 15.7233 |
| 0.0001        | 42.5063 | 850  | 0.1851          | 46.8208   | 12.9979 |
| 0.0           | 45.0    | 900  | 0.1887          | 47.9769   | 13.4172 |
| 0.0           | 47.5063 | 950  | 0.1904          | 47.9769   | 13.4172 |
| 0.0           | 50.0    | 1000 | 0.1916          | 49.1329   | 12.9979 |
| 0.0           | 52.5063 | 1050 | 0.1929          | 51.4451   | 14.8847 |
| 0.0           | 55.0    | 1100 | 0.1940          | 50.8671   | 14.8847 |
| 0.0           | 57.5063 | 1150 | 0.1951          | 50.8671   | 15.9329 |
| 0.0           | 60.0    | 1200 | 0.1961          | 50.8671   | 15.9329 |
| 0.0           | 62.5063 | 1250 | 0.1969          | 51.4451   | 15.9329 |
| 0.0           | 65.0    | 1300 | 0.1978          | 51.4451   | 15.9329 |
| 0.0           | 67.5063 | 1350 | 0.1986          | 51.4451   | 15.9329 |
| 0.0           | 70.0    | 1400 | 0.1994          | 51.4451   | 15.9329 |
| 0.0           | 72.5063 | 1450 | 0.2002          | 51.4451   | 15.9329 |
| 0.0           | 75.0    | 1500 | 0.2009          | 51.4451   | 15.9329 |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.6.0
- Datasets 3.2.0
- Tokenizers 0.21.0