---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-noisy-hindi-10dB
  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-small-noisy-hindi-10dB

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7442
- Wer: 41.8554

## 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: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 1.6146        | 0.61  | 50   | 1.3244          | 85.2585 |
| 0.8209        | 1.22  | 100  | 0.7607          | 55.4556 |
| 0.6434        | 1.83  | 150  | 0.6184          | 51.5822 |
| 0.5053        | 2.44  | 200  | 0.5191          | 46.7404 |
| 0.409         | 3.05  | 250  | 0.4271          | 41.9938 |
| 0.265         | 3.66  | 300  | 0.3151          | 39.4778 |
| 0.1786        | 4.27  | 350  | 0.2965          | 37.3076 |
| 0.1617        | 4.88  | 400  | 0.2826          | 36.2355 |
| 0.103         | 5.49  | 450  | 0.2877          | 35.5957 |
| 0.0907        | 6.1   | 500  | 0.2929          | 35.3450 |
| 0.0595        | 6.71  | 550  | 0.3032          | 34.8262 |
| 0.0338        | 7.32  | 600  | 0.3186          | 34.7743 |
| 0.0365        | 7.93  | 650  | 0.3303          | 34.3853 |
| 0.021         | 8.54  | 700  | 0.3414          | 34.3420 |
| 0.0174        | 9.15  | 750  | 0.3561          | 34.1605 |
| 0.0129        | 9.76  | 800  | 0.3619          | 34.3247 |
| 0.009         | 10.37 | 850  | 0.3681          | 33.9703 |
| 0.0082        | 10.98 | 900  | 0.3802          | 34.2469 |
| 0.006         | 11.59 | 950  | 0.3817          | 33.4083 |
| 0.0052        | 12.2  | 1000 | 0.4054          | 34.4112 |
| 0.005         | 12.8  | 1050 | 0.4113          | 34.2123 |
| 0.0041        | 13.41 | 1100 | 0.4139          | 33.8060 |
| 0.0043        | 14.02 | 1150 | 0.4161          | 32.9500 |
| 0.0028        | 14.63 | 1200 | 0.4284          | 33.0192 |
| 0.0027        | 15.24 | 1250 | 0.4349          | 33.1229 |
| 0.0027        | 15.85 | 1300 | 0.4253          | 32.7598 |
| 0.0022        | 16.46 | 1350 | 0.4419          | 33.1143 |
| 0.0023        | 17.07 | 1400 | 0.4453          | 32.9154 |
| 0.002         | 17.68 | 1450 | 0.4457          | 32.5696 |
| 0.0014        | 18.29 | 1500 | 0.4592          | 32.8809 |
| 0.0014        | 18.9  | 1550 | 0.4757          | 32.8290 |
| 0.001         | 19.51 | 1600 | 0.4767          | 33.4169 |
| 0.0008        | 20.12 | 1650 | 0.4876          | 32.4831 |
| 0.0008        | 20.73 | 1700 | 0.4905          | 32.9760 |
| 0.0011        | 21.34 | 1750 | 0.4876          | 32.7252 |
| 0.0007        | 21.95 | 1800 | 0.4992          | 33.0105 |
| 0.0003        | 22.56 | 1850 | 0.5190          | 32.3102 |
| 0.0007        | 23.17 | 1900 | 0.5240          | 32.6734 |
| 0.0005        | 23.78 | 1950 | 0.5315          | 32.8809 |
| 0.0003        | 24.39 | 2000 | 0.5333          | 32.7771 |
| 0.0002        | 25.0  | 2050 | 0.5441          | 32.1200 |
| 0.0001        | 25.61 | 2100 | 0.5626          | 32.4313 |
| 0.0001        | 26.22 | 2150 | 0.5690          | 32.1546 |
| 0.0001        | 26.83 | 2200 | 0.5861          | 32.1978 |
| 0.0001        | 27.44 | 2250 | 0.6071          | 32.0163 |
| 0.0           | 28.05 | 2300 | 0.6214          | 32.6388 |
| 0.0001        | 28.66 | 2350 | 0.6333          | 32.7512 |
| 0.0           | 29.27 | 2400 | 0.6525          | 32.5782 |
| 0.0           | 29.88 | 2450 | 0.6627          | 32.6647 |
| 0.0           | 30.49 | 2500 | 0.6759          | 32.5523 |
| 0.0           | 31.1  | 2550 | 0.6960          | 33.3737 |
| 0.0           | 31.71 | 2600 | 0.7087          | 34.1864 |
| 0.0           | 32.32 | 2650 | 0.7228          | 34.4544 |
| 0.0           | 32.93 | 2700 | 0.7274          | 35.1634 |
| 0.0           | 33.54 | 2750 | 0.7327          | 35.7254 |
| 0.0           | 34.15 | 2800 | 0.7369          | 37.0569 |
| 0.0           | 34.76 | 2850 | 0.7405          | 38.2155 |
| 0.0           | 35.37 | 2900 | 0.7433          | 40.8871 |
| 0.0           | 35.98 | 2950 | 0.7441          | 41.6739 |
| 0.0           | 36.59 | 3000 | 0.7442          | 41.8554 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 1.12.1
- Datasets 2.16.1
- Tokenizers 0.15.0