---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: whisper-large-v3-turbo-Telugu-Version1
  results: []
language:
- te
pipeline_tag: automatic-speech-recognition
---

<!-- 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-large-v3-turbo-Telugu-Version1

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8897
- Wer: 103.8462

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 20000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch     | Step  | Validation Loss | Wer      |
|:-------------:|:---------:|:-----:|:---------------:|:--------:|
| 0.0234        | 142.8571  | 2000  | 0.4991          | 98.3516  |
| 0.0024        | 285.7143  | 4000  | 0.6494          | 95.6044  |
| 0.0008        | 428.5714  | 6000  | 0.7260          | 95.0549  |
| 0.0004        | 571.4286  | 8000  | 0.7513          | 94.5055  |
| 0.0003        | 714.2857  | 10000 | 0.7775          | 95.0549  |
| 0.0002        | 857.1429  | 12000 | 0.8183          | 109.3407 |
| 0.0002        | 1000.0    | 14000 | 0.8304          | 92.3077  |
| 0.0001        | 1142.8571 | 16000 | 0.8528          | 96.1538  |
| 0.0001        | 1285.7143 | 18000 | 0.8839          | 100.0    |
| 0.0001        | 1428.5714 | 20000 | 0.8897          | 103.8462 |


### Framework versions

- PEFT 0.14.0
- Transformers 4.46.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.20.1