metadata

language:
  - multilingual
license: apache-2.0
base_model: openai/whisper-small
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: basic_train_basic_test_shuffle_250 300 1200 300 300
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: xbilek25/basic_train_basic_test_shuffle_250
          type: mozilla-foundation/common_voice_11_0
          args: 'config: csen, split: train'
        metrics:
          - name: Wer
            type: wer
            value: 18.07865388378008

basic_train_basic_test_shuffle_250 300 1200 300 300

This model is a fine-tuned version of openai/whisper-small on the xbilek25/basic_train_basic_test_shuffle_250 dataset. It achieves the following results on the evaluation set:

Loss: 0.0982
Wer: 18.0787

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: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 300
training_steps: 1200
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0006	2.04	300	0.0969	26.1006
0.0004	4.08	600	0.0986	25.1810
0.0002	7.02	900	0.0978	26.5310
0.0002	9.06	1200	0.0982	18.0787

Framework versions

Transformers 4.37.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2