---
language:
- es
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
base_model: openai/whisper-medium
model-index:
- name: Whisper Medium Es - Juan Carlos Piñeros
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: es
      split: test
      args: es
    metrics:
    - type: wer
      value: 5.421819787985865
      name: Wer
---

<!-- 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 Medium Es - Juan Carlos Piñeros

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1672
- Wer: 5.4218

Using the script provided in the Whisper Sprint (Dec. 2022) the models achieves these results on the evaluation sets (WER):
- google/fleurs: 5.88
- mozilla-foundation/common_voice_11_0: XXX

## 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: 16
- 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: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.0792        | 0.33  | 1000 | 0.1904          | 6.0493 |
| 0.0851        | 0.67  | 2000 | 0.1757          | 5.9558 |
| 0.0946        | 1.0   | 3000 | 0.1672          | 5.4218 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2