README.md

metadata

license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - lyhourt/clean_3
metrics:
  - wer
model-index:
  - name: whisper-small-clean_3-400
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: lyhourt/clean_3
          type: lyhourt/clean_3
        metrics:
          - name: Wer
            type: wer
            value: 4.053271569195136

whisper-small-clean_3-400

This model is a fine-tuned version of openai/whisper-small on the lyhourt/clean_3 dataset. It achieves the following results on the evaluation set:

• Loss: 0.0233
• Wer: 4.0533

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: 400
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0726	0.25	100	0.0732	11.2913
0.0477	0.5	200	0.0527	7.8170
0.0025	1.1425	300	0.0243	4.3428
0.0011	1.3925	400	0.0233	4.0533

Framework versions

• Transformers 4.41.0
• Pytorch 2.3.0+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1