---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: whisper-large-v3-turbo-Hindi-Version2
  results: []
language:
- hi
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-Hindi-Version2

This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2175
- Wer: 23.1550

## 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     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.2178        | 6.7797  | 2000  | 0.2245          | 25.6931 |
| 0.1841        | 13.5593 | 4000  | 0.2146          | 24.6095 |
| 0.1572        | 20.3390 | 6000  | 0.2121          | 23.5845 |
| 0.1489        | 27.1186 | 8000  | 0.2120          | 23.9848 |
| 0.1315        | 33.8983 | 10000 | 0.2118          | 23.6822 |
| 0.1253        | 40.6780 | 12000 | 0.2145          | 22.9793 |
| 0.1154        | 47.4576 | 14000 | 0.2154          | 23.1941 |
| 0.1151        | 54.2373 | 16000 | 0.2168          | 23.0964 |
| 0.1079        | 61.0169 | 18000 | 0.2175          | 23.1550 |


### Framework versions

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