---
language:
- hi
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- velocity-whisper-tiny
metrics:
- wer
model-index:
- name: whisper-tiny-finetuned-hinglish
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: whisper-training
      type: velocity-whisper-tiny
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 42.262816735415434
---

<!-- 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-tiny-finetuned-hinglish

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the whisper-training dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7758
- Wer: 42.2628

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step  | Validation Loss | Wer     |
|:-------------:|:-------:|:-----:|:---------------:|:-------:|
| 0.3632        | 1.7825  | 1000  | 0.3962          | 51.0784 |
| 0.2411        | 3.5651  | 2000  | 0.3428          | 45.1149 |
| 0.1242        | 5.3476  | 3000  | 0.3459          | 42.1685 |
| 0.0813        | 7.1301  | 4000  | 0.3610          | 42.1685 |
| 0.0654        | 8.9127  | 5000  | 0.3949          | 41.9210 |
| 0.0309        | 10.6952 | 6000  | 0.4422          | 42.7814 |
| 0.0161        | 12.4777 | 7000  | 0.4836          | 42.3925 |
| 0.0067        | 14.2602 | 8000  | 0.5291          | 42.9346 |
| 0.0032        | 16.0428 | 9000  | 0.5645          | 42.4514 |
| 0.0031        | 17.8253 | 10000 | 0.5951          | 42.7814 |
| 0.002         | 19.6078 | 11000 | 0.6248          | 42.5103 |
| 0.0007        | 21.3904 | 12000 | 0.6486          | 42.8167 |
| 0.0004        | 23.1729 | 13000 | 0.6760          | 42.0625 |
| 0.0008        | 24.9554 | 14000 | 0.6982          | 42.4396 |
| 0.0018        | 26.7380 | 15000 | 0.7149          | 42.4985 |
| 0.0002        | 28.5205 | 16000 | 0.7172          | 41.8739 |
| 0.0001        | 30.3030 | 17000 | 0.7307          | 42.4042 |
| 0.0001        | 32.0856 | 18000 | 0.7399          | 42.0742 |
| 0.0001        | 33.8681 | 19000 | 0.7497          | 42.1332 |
| 0.0001        | 35.6506 | 20000 | 0.7608          | 42.0860 |
| 0.0           | 37.4332 | 21000 | 0.7695          | 41.9682 |
| 0.0           | 39.2157 | 22000 | 0.7758          | 42.2628 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1