---
language:
- hi
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper_Samveg17@
  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_Samveg17@

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Google Fleurs  dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5117
- Wer: 37.9539

## 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: 8
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1401        | 4.72  | 1000 | 0.3607          | 39.9494 |
| 0.0174        | 9.43  | 2000 | 0.4239          | 38.9954 |
| 0.0022        | 14.15 | 3000 | 0.4867          | 38.4698 |
| 0.001         | 18.87 | 4000 | 0.5117          | 37.9539 |


### Framework versions

- Transformers 4.32.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3