---
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 v2 Spanish
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_11_0 es
      type: mozilla-foundation/common_voice_11_0
      config: es
      split: test
      args: es
    metrics:
    - name: Wer
      type: wer
      value: 5.288186684683748
---

<!-- 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 v2 Spanish

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the mozilla-foundation/common_voice_11_0 es dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1702
- Wer google/fleurs: 4.89
- Wer mozilla-foundation/common_voice_11_0: 5.2882

## 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: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.1738        | 0.1   | 1000  | 0.2031          | 7.0384 |
| 0.2108        | 1.01  | 2000  | 0.1885          | 6.6668 |
| 0.1599        | 1.11  | 3000  | 0.1814          | 6.5342 |
| 0.0794        | 2.01  | 4000  | 0.1792          | 6.0314 |
| 0.0477        | 2.11  | 5000  | 0.1936          | 6.1795 |
| 0.0341        | 3.02  | 6000  | 0.2038          | 6.0113 |
| 0.0264        | 3.12  | 7000  | 0.2111          | 5.8410 |
| 0.0608        | 4.02  | 8000  | 0.1824          | 5.9067 |
| 0.0523        | 4.12  | 9000  | 0.1768          | 5.3941 |
| 0.0984        | 5.03  | 10000 | 0.1702          | 5.2882 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 2.0.0.dev20221210+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2