README.md

metadata

license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - lyhourt/clean_6
metrics:
  - wer
model-index:
  - name: whisper-small-clean_6-v5
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: lyhourt/clean_6
          type: lyhourt/clean_6
        metrics:
          - name: Wer
            type: wer
            value: 21.24038237351364

whisper-small-clean_6-v5

This model is a fine-tuned version of openai/whisper-small on the lyhourt/clean_6 dataset. It achieves the following results on the evaluation set:

• Loss: 0.2706
• Wer: 21.2404

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: 50
• training_steps: 1500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1461	0.9452	500	0.2746	23.0473
0.0631	1.8904	1000	0.2693	21.5318
0.0334	2.8355	1500	0.2706	21.2404

Framework versions

• Transformers 4.41.2
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1