README.md

metadata

license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - generator
metrics:
  - wer
model-index:
  - name: ASR-small
    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: 0.569828722002635

ASR-small

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

• Loss: 2.2485
• Wer: 0.5698

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: 0.0005
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 300
• training_steps: 2000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
1.3412	0.5	1000	2.5398	0.7801
0.6222	1.46	2000	2.2485	0.5698

Framework versions

• Transformers 4.31.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.2
• Tokenizers 0.13.3