metadata

language:
  - eu
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_13_0
metrics:
  - wer
model-index:
  - name: Whisper Tiny 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: 34.086924983376655

Whisper Tiny Basque

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

Loss: 0.6509
Wer: 34.0869

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: 3.75e-05
train_batch_size: 256
eval_batch_size: 128
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
0.3011	23.26	1000	0.6017	41.4677
0.0904	46.51	2000	0.5919	35.6284
0.0408	69.77	3000	0.6267	34.7095
0.0265	93.02	4000	0.6420	34.3932
0.0212	116.28	5000	0.6509	34.0869

Framework versions

Transformers 4.37.2
Pytorch 2.2.0+cu121
Datasets 2.16.1
Tokenizers 0.15.1