metadata

library_name: transformers
language:
  - tk
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_17_0
metrics:
  - wer
model-index:
  - name: Whisper Small TK - Abdyrahman Gudratullayew
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 17.0
          type: mozilla-foundation/common_voice_17_0
          config: tk
          split: test
          args: 'config: tk, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 57.933673469387756

Whisper Small TK - Abdyrahman Gudratullayew

This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:

Loss: 1.3114
Wer: 57.9337

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: 16
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 5000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0083	14.0845	1000	1.1117	60.3571
0.0003	28.1690	2000	1.2099	57.7041
0.0002	42.2535	3000	1.2640	58.0102
0.0001	56.3380	4000	1.2973	58.1378
0.0001	70.4225	5000	1.3114	57.9337

Framework versions

Transformers 4.48.3
Pytorch 2.6.0+cu118
Datasets 3.2.0
Tokenizers 0.21.0