---
library_name: transformers
language:
- multilingual
license: apache-2.0
base_model: openai/whisper-medium
tags:
- hi,pa,ta,te,ml
- generated_from_trainer
datasets:
- google/fleurs
model-index:
- name: Whisper Medium FLEURS - Indic - Fine-tuning
  results: []
---

<!-- 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 Medium FLEURS - Indic - Fine-tuning

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the FLEURS dataset.

## 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: 32
- eval_batch_size: 32
- 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: 100
- training_steps: 3700
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0