metadata
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: []
Whisper Medium FLEURS - Indic - Fine-tuning
This model is a fine-tuned version of 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