metadata

datasets:
  - mozilla-foundation/common_voice_16_0
language:
  - hu
widget:
  - example_title: Sample 1
    src: >-
      https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample1.flac
  - example_title: Sample 2
    src: >-
      https://huggingface.co/datasets/Hungarians/samples/resolve/main/Sample2.flac
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: Whisper Medium Hu Cleaned
    results: []

Whisper Medium Hu - cleaned

This model is a fine-tuned version of openai/whisper-medium on the Common Voice 16.1 hu cleaned dataset. It achieves the following results on the evaluation set:

Loss: 0.0486
Wer Ortho: 5.5028
Wer: 4.9758

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: 6.25e-06
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 100
training_steps: 1000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.0708	0.69	200	0.0712	8.0529	7.4029
0.0279	1.37	400	0.0554	6.4034	5.8342
0.0138	2.06	600	0.0487	5.6875	5.1732
0.0077	2.75	800	0.0479	5.4467	4.8837
0.0037	3.43	1000	0.0486	5.5028	4.9758

Framework versions

Transformers 4.37.2
Pytorch 2.1.0+cu121
Datasets 2.17.0
Tokenizers 0.15.1