README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: openai/whisper-medium.en
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: rishabhjain16/infer_myst
          type: rishabhjain16/infer_myst
          config: en
          split: test
        metrics:
          - type: wer
            value: 12.1
            name: WER
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: rishabhjain16/infer_pfs
          type: rishabhjain16/infer_pfs
          config: en
          split: test
        metrics:
          - type: wer
            value: 31.29
            name: WER
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: rishabhjain16/infer_cmu
          type: rishabhjain16/infer_cmu
          config: en
          split: test
        metrics:
          - type: wer
            value: 2.27
            name: WER
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: rishabhjain16/infer_pf_italian
          type: rishabhjain16/infer_pf_italian
          config: en
          split: test
        metrics:
          - type: wer
            value: 77.38
            name: WER
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: rishabhjain16/infer_pf_german
          type: rishabhjain16/infer_pf_german
          config: en
          split: test
        metrics:
          - type: wer
            value: 125.37
            name: WER
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: rishabhjain16/infer_pf_swedish
          type: rishabhjain16/infer_pf_swedish
          config: en
          split: test
        metrics:
          - type: wer
            value: 138.95
            name: WER
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: rishabhjain16/infer_so_chinese
          type: rishabhjain16/infer_so_chinese
          config: en
          split: test
        metrics:
          - type: wer
            value: 33.32
            name: WER
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: rishabhjain16/libritts_dev_clean
          type: rishabhjain16/libritts_dev_clean
          config: en
          split: test
        metrics:
          - type: wer
            value: 6.13
            name: WER

openai/whisper-medium.en

This model is a fine-tuned version of openai/whisper-medium.en on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.3763
• Wer: 11.2832

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: 32
• 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: 500
• training_steps: 4000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2381	0.12	500	0.2625	11.4877
0.1332	1.1	1000	0.2451	11.4078
0.1097	2.08	1500	0.2610	11.5359
0.0412	3.06	2000	0.2804	10.9598
0.0219	4.04	2500	0.3426	10.9669
0.0139	5.02	3000	0.3503	11.3325
0.0086	6.0	3500	0.3761	11.0222
0.0017	6.13	4000	0.3763	11.2832

Framework versions

• Transformers 4.27.0.dev0
• Pytorch 1.13.1+cu117
• Datasets 2.9.1.dev0
• Tokenizers 0.13.2