metadata

language:
  - eu
license: apache-2.0
base_model: openai/whisper-small
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: Whisper Small Basque
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_13_0 eu
          type: mozilla-foundation/common_voice_13_0
          config: eu
          split: validation
          args: eu
        metrics:
          - name: Wer
            type: wer
            value: 19.351588788812993

Whisper Small Basque

This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_13_0 eu dataset. It achieves the following results on the evaluation set:

Loss: 0.3485
Wer: 19.3516

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: 64
eval_batch_size: 32
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: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.337	5.85	1000	0.3838	26.8815
0.1384	11.7	2000	0.3431	22.1544
0.0732	17.54	3000	0.3376	20.0447
0.0432	23.39	4000	0.3458	19.5349
0.0378	29.24	5000	0.3485	19.3516

Framework versions

Transformers 4.37.2
Pytorch 2.2.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1