---
language:
- es
license: apache-2.0
base_model: openai/whisper-base
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper base Spanish Improved
  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: 'config: es, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 20.435869264920363
---

<!-- 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 base Spanish Improved

This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the Common Voice 11.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3238
- Wer: 20.4359

## 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: 5e-06
- train_batch_size: 16
- eval_batch_size: 8
- 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: 8000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.3177        | 0.12  | 1000 | 0.3974          | 23.5886 |
| 0.294         | 0.25  | 2000 | 0.3681          | 22.2548 |
| 0.3409        | 0.38  | 3000 | 0.3512          | 21.6964 |
| 0.26          | 0.5   | 4000 | 0.3407          | 21.2621 |
| 0.3503        | 0.62  | 5000 | 0.3345          | 20.8259 |
| 0.3067        | 0.75  | 6000 | 0.3297          | 20.5207 |
| 0.2324        | 0.88  | 7000 | 0.3243          | 20.4956 |
| 0.3413        | 1.0   | 8000 | 0.3238          | 20.4359 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.15.0