transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer es dataset:ctam8736/papi_asr base_model:openai/whisper-tiny license:apache-2.0 model-index endpoints_compatible region:us
---
language:
- es
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- ctam8736/papi_asr
metrics:
- wer
model-index:
- name: Whisper Small Papi/Es
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: Papi ASR Test
      type: ctam8736/papi_asr
      args: 'config: es, split: test'
    metrics:
    - name: Wer
      type: wer
      value: 29.977162647125255
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small Papi/Es

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Papi ASR Test dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1243
- Wer: 29.9772

## 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: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.0881        | 0.34  | 200  | 0.1414          | 23.3066 |
| 0.0563        | 0.69  | 400  | 0.1388          | 23.8738 |
| 0.0416        | 1.03  | 600  | 0.1367          | 26.2630 |
| 0.044         | 1.38  | 800  | 0.1295          | 29.1289 |
| 0.0546        | 1.72  | 1000 | 0.1243          | 29.9772 |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0
