---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: juancopi81/whisper-medium-es
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Common Voice 11.0
      type: mozilla-foundation/common_voice_11_0
      config: es
      split: test
      args: es
    metrics:
    - name: Wer
      type: wer
      value: 5.945636921157944
---

<!-- 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. -->

# juancopi81/whisper-medium-es

This model is a fine-tuned version of [juancopi81/whisper-medium-es](https://huggingface.co/juancopi81/whisper-medium-es) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1893
- Wer: 5.9456

Using the script provided in the Whisper Sprint (Dec. 2022) the models achieves these results on the evaluation sets (WER):
- google/fleurs: 7.02
- mozilla-foundation/common_voice_11_0: XXXX

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.244         | 1.01  | 1000 | 0.1848          | 6.4894 |
| 0.0714        | 2.02  | 2000 | 0.1805          | 5.9528 |
| 0.0285        | 3.03  | 3000 | 0.1893          | 5.9456 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2