README.md

metadata

language:
  - he
license: apache-2.0
base_model: openai/whisper-base
tags:
  - generated_from_trainer
datasets:
  - Alex2575/heb_anna
metrics:
  - wer
model-index:
  - name: aleksis_heb_base
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: heb_anna
          type: Alex2575/heb_anna
        metrics:
          - name: Wer
            type: wer
            value: 8.770548282311251

aleksis_heb_base

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

• Loss: 0.1006
• Wer Ortho: 8.7616
• Wer: 8.7705

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: 1
• eval_batch_size: 16
• seed: 42
• gradient_accumulation_steps: 16
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant_with_warmup
• lr_scheduler_warmup_steps: 50
• training_steps: 500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.0584	4.24	500	0.1006	8.7616	8.7705

Framework versions

• Transformers 4.35.0.dev0
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.14.1