transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer es dataset:facebook/multilingual_librispeech base_model:openai/whisper-small license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- es
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- facebook/multilingual_librispeech
metrics:
- wer
model-index:
- name: Whisper Medium es - Dash Guitar
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: facebook/multilingual_librispeech
      type: facebook/multilingual_librispeech
      config: spanish
      split: test
      args: spanish
    metrics:
    - name: Wer
      type: wer
      value: 7.085875706214689
---

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# Whisper Medium es - Dash Guitar

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the facebook/multilingual_librispeech dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1535
- Wer Ortho: 7.0848
- Wer: 7.0859

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
| 0.3349        | 0.02  | 500  | 0.1782          | 8.1526    | 8.1571 |
| 0.309         | 0.04  | 1000 | 0.1702          | 7.5899    | 7.5921 |
| 0.2814        | 0.05  | 1500 | 0.1680          | 8.0103    | 8.0124 |
| 0.3067        | 0.07  | 2000 | 0.1665          | 8.1007    | 8.1028 |
| 0.3223        | 0.09  | 2500 | 0.1751          | 9.2272    | 9.2294 |
| 0.2696        | 0.11  | 3000 | 0.1583          | 7.2374    | 7.2395 |
| 0.3203        | 0.13  | 3500 | 0.1542          | 6.9560    | 6.9559 |
| 0.2655        | 0.14  | 4000 | 0.1535          | 7.0848    | 7.0859 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.0
