---
language:
- es
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small Vi - Shiv Kumar Ganesh
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: vi
      split: test
      args: vi
    metrics:
    - name: Wer
      type: wer
      value: 46.676902829567894
---

<!-- 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 Vi - Shiv Kumar Ganesh

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: 0.7220
- Wer: 46.6769

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1200
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.7433        | 1.02  | 100  | 1.6824          | 155.0559 |
| 0.5929        | 2.04  | 200  | 0.8475          | 55.5824  |
| 0.1188        | 3.05  | 300  | 0.6646          | 47.2801  |
| 0.0672        | 5.0   | 400  | 0.7099          | 61.3292  |
| 0.0317        | 6.02  | 500  | 0.6951          | 49.9013  |
| 0.0169        | 7.04  | 600  | 0.7658          | 62.8866  |
| 0.0089        | 8.06  | 700  | 0.6681          | 34.2509  |
| 0.004         | 10.01 | 800  | 0.6875          | 43.8364  |
| 0.0015        | 11.03 | 900  | 0.7129          | 46.8195  |
| 0.0011        | 12.04 | 1000 | 0.7194          | 47.4775  |
| 0.0011        | 13.06 | 1100 | 0.7217          | 46.1505  |
| 0.001         | 15.01 | 1200 | 0.7220          | 46.6769  |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu116
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2