---
language:
- es
license: apache-2.0
base_model: openai/whisper-medium
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Medium Spanish
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: mozilla-foundation/common_voice_13_0 es
      type: mozilla-foundation/common_voice_13_0
      config: es
      split: test
      args: es
    metrics:
    - name: Wer
      type: wer
      value: 5.408751772230669
---

<!-- 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 Spanish

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_13_0 es dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1915
- Wer: 5.4088

## 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: 64
- eval_batch_size: 32
- 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

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0917        | 2.0   | 1000  | 0.1944          | 6.8560 |
| 0.0927        | 4.0   | 2000  | 0.1817          | 6.1439 |
| 0.0456        | 6.01  | 3000  | 0.1805          | 6.2626 |
| 0.0343        | 8.01  | 4000  | 0.2097          | 6.1773 |
| 0.0046        | 10.01 | 5000  | 0.2292          | 5.9374 |
| 0.0829        | 12.01 | 6000  | 0.1814          | 6.0644 |
| 0.0021        | 14.01 | 7000  | 0.2318          | 5.7096 |
| 0.0288        | 16.01 | 8000  | 0.1871          | 5.5755 |
| 0.1297        | 18.02 | 9000  | 0.1831          | 5.6885 |
| 0.0377        | 20.02 | 10000 | 0.1915          | 5.4088 |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3