transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer es dataset:coser_turnos/canario 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:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- coser_turnos/canario
metrics:
- wer
model-index:
- name: Whisper Small Canario - Johnatan E. Bonilla
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: COSER Canario 1.0
      type: coser_turnos/canario
      args: 'config: cana, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 86.48078372268274
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small Canario - Johnatan E. Bonilla

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the COSER Canario 1.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2760
- Wer: 86.4808

## 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: 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: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3041        | 3.95  | 1000 | 0.8140          | 104.0241 |
| 0.0471        | 7.91  | 2000 | 1.0680          | 109.6910 |
| 0.0238        | 11.86 | 3000 | 1.2071          | 92.1929  |
| 0.013         | 15.81 | 4000 | 1.2760          | 86.4808  |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.0
