.ipynb_checkpoints/README-checkpoint.md

metadata

language:
  - et
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small et - Common Voice+FLEURS
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0, FLEURS
          type: mozilla-foundation/common_voice_11_0
          config: et
          split: train
        metrics:
          - name: Wer
            type: wer
            value: 42.48444526581655

Whisper Small et - Common Voice+FLEURS

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0, FLEURS dataset. It achieves the following results on the evaluation set:

• Loss: 0.8754
• Wer: 42.4844

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
0.0094	10.0	1000	0.7125	43.4085
0.0024	20.01	2000	0.7960	42.1795
0.0012	30.01	3000	0.8237	41.8961
0.0006	40.02	4000	0.8627	41.7853
0.0004	51.0	5000	0.8754	42.4844

Framework versions

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