---
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 Large Es - Javier Alonso
  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: 5.520113299724547
---

<!-- 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 Large Es - Javier Alonso

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1571
- Wer: 5.5201

## 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: 2
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.211         | 0.1   | 1000  | 0.2293          | 8.3896 |
| 0.2227        | 0.2   | 2000  | 0.2215          | 8.2552 |
| 0.1496        | 0.3   | 3000  | 0.2121          | 8.0362 |
| 0.1851        | 0.4   | 4000  | 0.2018          | 7.5197 |
| 0.1917        | 0.5   | 5000  | 0.1916          | 7.1098 |
| 0.1857        | 0.6   | 6000  | 0.1817          | 6.5537 |
| 0.1294        | 0.7   | 7000  | 0.1752          | 6.4062 |
| 0.1358        | 0.8   | 8000  | 0.1670          | 5.9950 |
| 0.1542        | 0.9   | 9000  | 0.1604          | 5.7858 |
| 0.1554        | 1.0   | 10000 | 0.1571          | 5.5201 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.10.0+cu111
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2