---
language:
- mar
license: apache-2.0
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: whisper_marathi_small_V1
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: mr
      split: test
      args: 'config: hi, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 45.00676938946554
---

<!-- 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_marathi_small_V1

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: 0.2754
- Wer: 45.0068

## 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: 10
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.4794        | 0.41  | 100  | 0.4754          | 59.9317 |
| 0.3121        | 0.81  | 200  | 0.3161          | 52.8786 |
| 0.2051        | 1.22  | 300  | 0.2900          | 50.2547 |
| 0.1887        | 1.63  | 400  | 0.2779          | 48.1336 |
| 0.16          | 2.03  | 500  | 0.2679          | 46.2639 |
| 0.1131        | 2.44  | 600  | 0.2706          | 45.8449 |
| 0.1128        | 2.85  | 700  | 0.2658          | 45.1551 |
| 0.0678        | 3.25  | 800  | 0.2763          | 45.2195 |
| 0.075         | 3.66  | 900  | 0.2769          | 45.7611 |
| 0.0609        | 4.07  | 1000 | 0.2754          | 45.0068 |


### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2