---
library_name: transformers
language:
- hi
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: 'Whisper Medium Hi - Illuminati014 '
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common_voice_modified
      type: mozilla-foundation/common_voice_11_0
      config: hi
      split: None
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 31.030015115525806
---

<!-- 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 Hi - Illuminati014 

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common_voice_modified dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5733
- Wer: 31.0300

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.0087        | 12.1951 | 1000 | 0.4534          | 32.1961 |
| 0.0004        | 24.3902 | 2000 | 0.5305          | 31.3755 |
| 0.0001        | 36.5854 | 3000 | 0.5546          | 30.9652 |
| 0.0001        | 48.7805 | 4000 | 0.5733          | 31.0300 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0