transformers pytorch whisper automatic-speech-recognition whisper-event generated_from_trainer es dataset:mozilla-foundation/common_voice_13_0 base_model:openai/whisper-large license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- es
license: apache-2.0
base_model: openai/whisper-large
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
model-index:
- name: Whisper Large 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: 5.126477928109984
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Large Spanish

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the mozilla-foundation/common_voice_13_0 es dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2663
- Wer: 5.1265

## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 20000

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.0834        | 2.0   | 1000  | 0.1862          | 6.3852 |
| 0.0871        | 4.0   | 2000  | 0.1777          | 5.9175 |
| 0.039         | 6.0   | 3000  | 0.1780          | 5.7423 |
| 0.0265        | 8.0   | 4000  | 0.2121          | 5.7744 |
| 0.0059        | 10.0  | 5000  | 0.2219          | 5.8097 |
| 0.0855        | 12.01 | 6000  | 0.1839          | 5.9778 |
| 0.0037        | 14.01 | 7000  | 0.2273          | 5.8565 |
| 0.0293        | 16.01 | 8000  | 0.1965          | 5.8078 |
| 0.1174        | 18.01 | 9000  | 0.1984          | 5.8893 |
| 0.0355        | 20.01 | 10000 | 0.2136          | 5.8662 |
| 0.0279        | 22.01 | 11000 | 0.1882          | 5.4960 |
| 0.0043        | 24.01 | 12000 | 0.2444          | 5.3356 |
| 0.0302        | 26.01 | 13000 | 0.2223          | 5.4620 |
| 0.0011        | 28.01 | 14000 | 0.2603          | 5.5608 |
| 0.001         | 30.01 | 15000 | 0.2452          | 5.3087 |
| 0.0003        | 32.01 | 16000 | 0.2573          | 5.3523 |
| 0.0004        | 34.02 | 17000 | 0.2690          | 5.2952 |
| 0.0013        | 36.02 | 18000 | 0.2373          | 5.1438 |
| 0.0004        | 38.02 | 19000 | 0.2618          | 5.1361 |
| 0.0004        | 40.02 | 20000 | 0.2663          | 5.1265 |


### Framework versions

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