metadata

language:
  - hr
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - parlaSmall
metrics:
  - wer
model-index:
  - name: Whisper Small Croatian
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: parlaSmall_subset
          type: parlaSmall
          config: default
          split: None
          args: 'config: hr, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 25.440806045340054

Whisper Small Croatian

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

Loss: 0.5739
Wer: 25.4408

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: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0003	32.52	1000	0.5073	25.0630
0.0001	65.04	2000	0.5470	25.5668
0.0001	97.56	3000	0.5668	25.0630
0.0	130.08	4000	0.5739	25.4408

Framework versions

Transformers 4.39.3
Pytorch 2.0.0
Datasets 2.19.1
Tokenizers 0.15.1