---
library_name: transformers
language:
- ta
license: apache-2.0
base_model: Singhamarjeet8130/whisper-medium-hi
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Medium Hi ta - Amarjeet
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 13.0
      type: mozilla-foundation/common_voice_13_0
      config: ta
      split: test
      args: 'config: ta, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 37.38483391323612
---

<!-- 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 ta - Amarjeet

This model is a fine-tuned version of [Singhamarjeet8130/whisper-medium-hi](https://huggingface.co/Singhamarjeet8130/whisper-medium-hi) on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1794
- Wer: 37.3848

## 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: 16
- 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer     |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.133         | 0.2894 | 1000 | 0.2347          | 45.2937 |
| 0.1146        | 0.5787 | 2000 | 0.2040          | 41.4025 |
| 0.099         | 0.8681 | 3000 | 0.1835          | 38.8261 |
| 0.0652        | 1.1574 | 4000 | 0.1794          | 37.3848 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0