README.md

metadata

license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_9_0
metrics:
  - wer
model-index:
  - name: yt-special-batch8-tiny
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: mozilla-foundation/common_voice_9_0 id
          type: mozilla-foundation/common_voice_9_0
          config: id
          split: train
          args: id
        metrics:
          - name: Wer
            type: wer
            value: 5.397983265393693

yt-special-batch8-tiny

This model is a fine-tuned version of openai/whisper-tiny on the mozilla-foundation/common_voice_9_0 id dataset. It achieves the following results on the evaluation set:

• Loss: 0.0883
• Wer: 5.3980

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: 8
• eval_batch_size: 4
• 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: 5000

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.4292	1.58	1000	2.7893	302.9157
1.7988	3.17	2000	1.5463	110.1652
1.083	4.75	3000	0.7805	76.9320
0.3718	6.34	4000	0.3192	20.5964
0.1292	7.92	5000	0.0883	5.3980

Framework versions

• Transformers 4.31.0.dev0
• Pytorch 2.0.1+cu117
• Datasets 2.13.1
• Tokenizers 0.13.3