---
library_name: transformers
language:
- te
base_model: kattojuprashanth238/whisper-small-te-v6
tags:
- generated_from_trainer
datasets:
- Harveenchadha/indic-voice
metrics:
- wer
model-index:
- name: Whisper Small Te - Prashanth Kattoju
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: indic-voice
      type: Harveenchadha/indic-voice
      config: te
      split: None
    metrics:
    - name: Wer
      type: wer
      value: 18.39201261166579
---

<!-- 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-v6](https://huggingface.co/kattojuprashanth238/whisper-small-te-v6) on the indic-voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2445
- Wer Ortho: 50.9174
- Wer: 18.3920

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- 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     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 0.1999        | 0.3788 | 100  | 0.2231          | 62.9969   | 20.0210 |
| 0.1478        | 0.7576 | 200  | 0.1937          | 53.3639   | 18.5497 |
| 0.0719        | 1.1364 | 300  | 0.2053          | 52.2936   | 18.9175 |
| 0.0851        | 1.5152 | 400  | 0.1674          | 51.0703   | 16.7630 |
| 0.0682        | 1.8939 | 500  | 0.1752          | 53.5168   | 17.2359 |
| 0.035         | 2.2727 | 600  | 0.1967          | 50.0      | 20.0210 |
| 0.0348        | 2.6515 | 700  | 0.2017          | 53.5168   | 17.9191 |
| 0.0298        | 3.0303 | 800  | 0.2034          | 51.0703   | 17.4461 |
| 0.0202        | 3.4091 | 900  | 0.2225          | 55.1988   | 17.9716 |
| 0.02          | 3.7879 | 1000 | 0.2486          | 56.8807   | 21.1771 |
| 0.0133        | 4.1667 | 1100 | 0.2436          | 55.6575   | 23.3841 |
| 0.0136        | 4.5455 | 1200 | 0.2337          | 54.1284   | 19.6532 |
| 0.0116        | 4.9242 | 1300 | 0.2502          | 56.2691   | 21.0194 |
| 0.0117        | 5.3030 | 1400 | 0.2338          | 50.0      | 18.1293 |
| 0.0158        | 5.6818 | 1500 | 0.2445          | 50.9174   | 18.3920 |


### Framework versions

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