README.md

metadata

license: apache-2.0
language:
  - eu
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - common_voice_11_0
metrics:
  - wer
model-index:
  - name: openai/whisper-small
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_11_0
          type: common_voice_11_0
          config: eu
          split: test
          args: eu
        metrics:
          - name: Wer
            type: wer
            value: 19.766305675433596

openai/whisper-small Basque-Euskera

This model is a fine-tuned version of openai/whisper-small on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:

• Loss: 0.4485
• Wer: 19.7663

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
0.048	4.04	1000	0.3402	21.7816
0.0047	9.03	2000	0.3862	20.1694
0.0012	14.02	3000	0.4221	19.7419
0.0008	19.02	4000	0.4411	19.7174
0.0006	24.01	5000	0.4485	19.7663

Framework versions

• Transformers 4.26.0.dev0
• Pytorch 1.13.0+cu117
• Datasets 2.7.1.dev0
• Tokenizers 0.13.2