README.md

metadata

language:
  - he
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - OverloadedOperator/tests-101
metrics:
  - wer
model-index:
  - name: Whisper Small He
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: TestDS
          type: OverloadedOperator/tests-101
          config: default
          split: validation
          args: 'config: he, split: validation'
        metrics:
          - name: Wer
            type: wer
            value: 0

Whisper Small He

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

• Loss: 0.0000
• Wer: 0.0

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: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0	1000.0	1000	0.0000	0.0
0.0	2000.0	2000	0.0000	0.0
0.0	3000.0	3000	0.0000	0.0
0.0	4000.0	4000	0.0000	0.0

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.0