metadata

license: apache-2.0
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: openai/whisper-medium
    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: 12.22
            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: 2.98
            name: WER
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: rishabhjain16/infer_cmu_9h
          type: rishabhjain16/infer_cmu_9h
          config: en
          split: test
        metrics:
          - type: wer
            value: 16.05
            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: 5.4
            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: 14.08
            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: 51.53
            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: 16.52
            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: 22.8
            name: WER

openai/whisper-medium

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

Loss: 0.3896
Wer: 200.1910

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
0.2328	0.12	500	0.2655	301.5949
0.1838	1.11	1000	0.2496	286.1977
0.1757	2.1	1500	0.2563	118.9213
0.0254	3.09	2000	0.2992	237.0841
0.0282	4.07	2500	0.3342	125.1999
0.0229	5.06	3000	0.3502	268.7414
0.0027	6.05	3500	0.3918	107.5536
0.003	7.03	4000	0.3896	200.1910

Framework versions

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