metadata

language:
  - ckb
  - ku
license: apache-2.0
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
  - google/fleurs
metrics:
  - wer
  - cer
model-index:
  - name: Whisper Small Ckb - Razhan Hameed
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: ckb
          split: test
        metrics:
          - type: wer
            value: 33.2192952446117
            name: Wer
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: razhan/asosoft-speech
          type: razhan/asosoft-speech
          config: ckb
          split: test
        metrics:
          - type: wer
            value: 31.94
            name: WER
          - type: cer
            value: 5.65
            name: CER

Whisper Small Ckb - Razhan Hameed

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:

Loss: 0.3825
Wer: 33.2193

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: 64
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: 12000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1693	2.49	1000	0.2060	39.1265
0.0722	4.98	2000	0.2124	36.3173
0.0127	7.46	3000	0.2736	36.5568
0.008	9.95	4000	0.3131	35.7015
0.0032	12.44	5000	0.3434	35.3936
0.0028	14.93	6000	0.3453	35.9258
0.003	17.41	7000	0.3558	34.9565
0.0022	19.9	8000	0.3593	34.2722
0.0016	22.39	9000	0.3639	34.3369
0.0015	24.88	10000	0.3785	34.0062
0.0009	27.36	11000	0.3915	34.2951
0.0001	29.85	12000	0.3825	33.2193

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu117
Datasets 2.7.1.dev0
Tokenizers 0.13.2