---
language:
- or
license: afl-3.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper_Small_Odia_CV_11.0_5k_steps
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 or
      type: mozilla-foundation/common_voice_11_0
      config: or
      split: test
      args: or
    metrics:
    - name: Wer
      type: wer
      value: 23.497884344146687
---

<!-- 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_Odia_CV_11.0_5k_steps

This model is a fine-tuned version of [Ranjit/Whisper_Small_Odia_10k_steps](https://huggingface.co/Ranjit/Whisper_Small_Odia_10k_steps) on the mozilla-foundation/common_voice_11_0 or dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4827
- Wer: 23.4979

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 5000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0018        | 50.0  | 1000 | 0.3315          | 24.0903 |
| 0.0           | 100.0 | 2000 | 0.4098          | 23.7236 |
| 0.0           | 150.0 | 3000 | 0.4827          | 23.4979 |
| 0.0           | 200.0 | 4000 | 0.4914          | 23.8928 |
| 0.0           | 250.0 | 5000 | 0.4953          | 23.7800 |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2