---
library_name: transformers
language:
- te
base_model: openai/whisper-small-v5
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small Te - Prashanth Kattoju
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 17
      type: mozilla-foundation/common_voice_17_0
      config: te
      split: test
      args: te
    metrics:
    - name: Wer
      type: wer
      value: 10.622710622710622
---

<!-- 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 [openai/whisper-small-v5](https://huggingface.co/openai/whisper-small-v5) on the Common Voice 17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0948
- Wer Ortho: 32.4176
- Wer: 10.6227

## 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: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use 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     |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:-------:|
| 1.4434        | 0.4338  | 50   | 0.9813          | 101.6484  | 70.6960 |
| 0.6517        | 0.8677  | 100  | 0.4498          | 81.8681   | 31.6850 |
| 0.3973        | 1.2950  | 150  | 0.3015          | 75.2747   | 28.3883 |
| 0.2864        | 1.7289  | 200  | 0.1763          | 65.9341   | 23.4432 |
| 0.1998        | 2.1562  | 250  | 0.1545          | 59.3407   | 21.2454 |
| 0.1631        | 2.5900  | 300  | 0.1231          | 53.2967   | 19.4139 |
| 0.1368        | 3.0174  | 350  | 0.1128          | 50.0      | 20.3297 |
| 0.0823        | 3.4512  | 400  | 0.1249          | 48.3516   | 16.6667 |
| 0.0795        | 3.8850  | 450  | 0.1094          | 48.3516   | 18.6813 |
| 0.0486        | 4.3124  | 500  | 0.1131          | 43.9560   | 17.7656 |
| 0.0386        | 4.7462  | 550  | 0.1044          | 43.9560   | 15.7509 |
| 0.0275        | 5.1735  | 600  | 0.1020          | 35.1648   | 16.3004 |
| 0.0323        | 5.6074  | 650  | 0.1050          | 43.4066   | 15.9341 |
| 0.0257        | 6.0347  | 700  | 0.1067          | 39.0110   | 14.6520 |
| 0.0196        | 6.4685  | 750  | 0.1096          | 39.0110   | 13.9194 |
| 0.0231        | 6.9024  | 800  | 0.1158          | 41.2088   | 14.8352 |
| 0.0213        | 7.3297  | 850  | 0.0915          | 39.0110   | 15.3846 |
| 0.0142        | 7.7636  | 900  | 0.1107          | 41.2088   | 15.3846 |
| 0.0129        | 8.1909  | 950  | 0.1132          | 37.9121   | 14.4689 |
| 0.01          | 8.6247  | 1000 | 0.1190          | 35.7143   | 13.7363 |
| 0.0123        | 9.0521  | 1050 | 0.1081          | 37.9121   | 14.4689 |
| 0.0144        | 9.4859  | 1100 | 0.1086          | 39.0110   | 14.2857 |
| 0.0115        | 9.9197  | 1150 | 0.1021          | 37.9121   | 16.6667 |
| 0.0097        | 10.3471 | 1200 | 0.0998          | 34.0659   | 14.1026 |
| 0.0075        | 10.7809 | 1250 | 0.0976          | 28.5714   | 10.8059 |
| 0.0062        | 11.2082 | 1300 | 0.1252          | 34.6154   | 12.6374 |
| 0.0081        | 11.6421 | 1350 | 0.1029          | 31.3187   | 13.7363 |
| 0.0058        | 12.0694 | 1400 | 0.0986          | 34.6154   | 11.9048 |
| 0.0092        | 12.5033 | 1450 | 0.1020          | 32.9670   | 13.7363 |
| 0.0047        | 12.9371 | 1500 | 0.0948          | 32.4176   | 10.6227 |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.0