README.md

metadata

library_name: transformers
license: mit
base_model: distil-whisper/distil-small.en
tags:
  - generated_from_trainer
datasets:
  - generator
metrics:
  - wer
model-index:
  - name: distil_whisper_en
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: generator
          type: generator
          config: default
          split: train
          args: default
        metrics:
          - name: Wer
            type: wer
            value: 0.8298755186721992

distil_whisper_en

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

• Loss: 0.0000
• Wer: 0.8299

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: 0.0001
• train_batch_size: 2
• eval_batch_size: 8
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 4
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0	19.031	500	0.0000	0.8299

Framework versions

• Transformers 4.44.2
• Pytorch 2.5.0+cu121
• Datasets 3.0.2
• Tokenizers 0.19.1