metadata

license: apache-2.0
base_model: openai/whisper-base
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_9_0
metrics:
  - wer
model-index:
  - name: yt-special-batch8-base
    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: 11.4438961596224

yt-special-batch8-base

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

Loss: 0.4155
Wer: 11.4439

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
41.113	1.58	1000	42.9759	107.5628
17.3442	3.17	2000	18.7037	144.1064
10.8061	4.75	3000	7.1531	52.5510
3.3269	6.34	4000	3.1035	47.0586
0.7405	7.92	5000	0.4155	11.4439

Framework versions

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