---
license: apache-2.0
base_model: openai/whisper-small
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- arrow
metrics:
- wer
model-index:
- name: whisper-small-indian_eng
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: arrow
      type: arrow
      config: default
      split: validation
      args: default
    metrics:
    - name: Wer
      type: wer
      value: 16.853932584269664
---

<!-- 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 the arrow dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7659
- Wer: 16.8539

## 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: 8
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 25
- training_steps: 200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.515         | 10.0  | 50   | 1.0232          | 16.8539 |
| 0.1717        | 20.0  | 100  | 0.7364          | 19.1011 |
| 0.0006        | 30.0  | 150  | 0.7300          | 15.7303 |
| 0.0003        | 40.0  | 200  | 0.7659          | 16.8539 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.19.1