---
language:
- hi
license: apache-2.0
library_name: peft
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
base_model: openai/whisper-small
model-index:
- name: Whisper Small hi 2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small hi 2

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3689

## 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: 0.001
- train_batch_size: 16
- 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 0.0   | 1    | 2.2900          |
| 0.5292        | 1.22  | 500  | 0.3877          |
| 0.2389        | 2.44  | 1000 | 0.3418          |
| 0.1726        | 3.67  | 1500 | 0.3191          |
| 0.1228        | 4.89  | 2000 | 0.3221          |
| 0.076         | 6.11  | 2500 | 0.3478          |
| 0.0399        | 7.33  | 3000 | 0.3689          |


### Framework versions

- PEFT 0.10.1.dev0
- Transformers 4.40.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2