metadata

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

Whisper Small Papi/Es

This model is a fine-tuned version of 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