metadata
language:
- cr
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: whisper-large-v3-croarian
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: audiofolder
type: audiofolder
config: default
split: train
args: 'config: cr, split: test'
metrics:
- name: Wer
type: wer
value: 64.14943295530352
whisper-large-v3-croarian
This model is a fine-tuned version of openai/whisper-large-v3 on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 1.7755
- Wer: 64.1494
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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0169 | 22.73 | 1000 | 1.3990 | 48.7258 |
| 0.0005 | 45.45 | 2000 | 1.6605 | 56.3042 |
| 0.0002 | 68.18 | 3000 | 1.7494 | 61.4410 |
| 0.0001 | 90.91 | 4000 | 1.7755 | 64.1494 |
Framework versions
- Transformers 4.36.1
- Pytorch 2.1.1+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0