---
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-indian_eng
  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-indian_eng

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3169
- Wer: 10.6061

## 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: 100
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.5504        | 1.5873  | 100  | 0.4581          | 10.6061 |
| 0.058         | 3.1746  | 200  | 0.2114          | 8.8154  |
| 0.0126        | 4.7619  | 300  | 0.2365          | 8.1267  |
| 0.0078        | 6.3492  | 400  | 0.2513          | 7.9890  |
| 0.0026        | 7.9365  | 500  | 0.2596          | 7.1625  |
| 0.0027        | 9.5238  | 600  | 0.2676          | 8.1267  |
| 0.0031        | 11.1111 | 700  | 0.2842          | 7.3003  |
| 0.0013        | 12.6984 | 800  | 0.2707          | 18.7328 |
| 0.0004        | 14.2857 | 900  | 0.2814          | 13.6364 |
| 0.0006        | 15.8730 | 1000 | 0.2806          | 11.1570 |
| 0.0009        | 17.4603 | 1100 | 0.2906          | 11.0193 |
| 0.0004        | 19.0476 | 1200 | 0.2948          | 11.1570 |
| 0.0003        | 20.6349 | 1300 | 0.2984          | 10.8815 |
| 0.0002        | 22.2222 | 1400 | 0.3008          | 10.8815 |
| 0.0003        | 23.8095 | 1500 | 0.2992          | 10.7438 |
| 0.0001        | 25.3968 | 1600 | 0.3040          | 10.8815 |
| 0.0002        | 26.9841 | 1700 | 0.3088          | 10.7438 |
| 0.0001        | 28.5714 | 1800 | 0.3077          | 10.6061 |
| 0.0001        | 30.1587 | 1900 | 0.3098          | 10.4683 |
| 0.0001        | 31.7460 | 2000 | 0.3111          | 10.4683 |
| 0.0001        | 33.3333 | 2100 | 0.3119          | 10.4683 |
| 0.0001        | 34.9206 | 2200 | 0.3129          | 10.4683 |
| 0.0001        | 36.5079 | 2300 | 0.3142          | 10.4683 |
| 0.0001        | 38.0952 | 2400 | 0.3146          | 10.4683 |
| 0.0001        | 39.6825 | 2500 | 0.3153          | 10.6061 |
| 0.0001        | 41.2698 | 2600 | 0.3158          | 10.6061 |
| 0.0001        | 42.8571 | 2700 | 0.3162          | 10.6061 |
| 0.0001        | 44.4444 | 2800 | 0.3167          | 10.6061 |
| 0.0001        | 46.0317 | 2900 | 0.3169          | 10.6061 |
| 0.0001        | 47.6190 | 3000 | 0.3169          | 10.6061 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.0.0
- Datasets 2.16.1
- Tokenizers 0.19.1