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

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: 1.6842
- Wer: 76.4655

## 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      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.5492        | 0.61  | 50   | 2.2588          | 122.9379 |
| 1.6655        | 1.22  | 100  | 1.6099          | 92.4434  |
| 1.4463        | 1.83  | 150  | 1.4333          | 89.4086  |
| 1.2723        | 2.44  | 200  | 1.3012          | 90.1954  |
| 1.1433        | 3.05  | 250  | 1.1803          | 84.7052  |
| 0.9489        | 3.66  | 300  | 1.0427          | 82.0768  |
| 0.8082        | 4.27  | 350  | 0.9796          | 81.3246  |
| 0.7696        | 4.88  | 400  | 0.9372          | 78.6962  |
| 0.631         | 5.49  | 450  | 0.9229          | 78.2898  |
| 0.5784        | 6.1   | 500  | 0.9306          | 76.3790  |
| 0.5112        | 6.71  | 550  | 0.9158          | 76.3963  |
| 0.3738        | 7.32  | 600  | 0.9585          | 75.7652  |
| 0.3762        | 7.93  | 650  | 0.9530          | 75.5490  |
| 0.2647        | 8.54  | 700  | 1.0094          | 76.1975  |
| 0.2282        | 9.15  | 750  | 1.0548          | 76.8632  |
| 0.1865        | 9.76  | 800  | 1.0789          | 76.4482  |
| 0.1172        | 10.37 | 850  | 1.1491          | 78.1688  |
| 0.1181        | 10.98 | 900  | 1.1769          | 76.5520  |
| 0.0778        | 11.59 | 950  | 1.2255          | 77.5117  |
| 0.0579        | 12.2  | 1000 | 1.3021          | 76.0246  |
| 0.0515        | 12.8  | 1050 | 1.3064          | 76.8546  |
| 0.0324        | 13.41 | 1100 | 1.3766          | 77.1140  |
| 0.0317        | 14.02 | 1150 | 1.4044          | 78.2206  |
| 0.0227        | 14.63 | 1200 | 1.4420          | 77.9353  |
| 0.0174        | 15.24 | 1250 | 1.4780          | 76.4482  |
| 0.0164        | 15.85 | 1300 | 1.5044          | 76.2494  |
| 0.0121        | 16.46 | 1350 | 1.5338          | 76.7595  |
| 0.0128        | 17.07 | 1400 | 1.5588          | 76.9410  |
| 0.0108        | 17.68 | 1450 | 1.5688          | 76.4482  |
| 0.0085        | 18.29 | 1500 | 1.6060          | 76.6903  |
| 0.0082        | 18.9  | 1550 | 1.6368          | 76.5606  |
| 0.0065        | 19.51 | 1600 | 1.6483          | 76.5520  |
| 0.0062        | 20.12 | 1650 | 1.6842          | 76.4655  |


### Framework versions

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