metadata

language:
  - cs
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: Whisper small + 2000 csen p5 concacat
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Prvni fine tuning spolecnych speakeru
          type: mozilla-foundation/common_voice_11_0
          args: 'config: csen, split: train'
        metrics:
          - name: Wer
            type: wer
            value: 32.2286109123214

Whisper small + 2000 csen p5 concacat

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

Loss: 0.5955
Wer: 32.2286

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: 100
training_steps: 800
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2369	1.09	200	0.5234	35.9820
0.0817	3.03	400	0.5461	35.6588
0.0192	4.12	600	0.5798	32.1176
0.011	6.06	800	0.5955	32.2286

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.18.0
Tokenizers 0.15.2