metadata
library_name: transformers
language:
- sr
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper - Serbian Model
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: sr
split: None
args: sr
metrics:
- name: Wer
type: wer
value: 26.91173920582625
Whisper - Serbian Model
This model is a fine-tuned version of openai/whisper-small on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4936
- Wer: 26.9117
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 |
|---|---|---|---|---|
| 0.0366 | 4.6083 | 1000 | 0.3116 | 27.6227 |
| 0.002 | 9.2166 | 2000 | 0.4394 | 27.1892 |
| 0.0003 | 13.8249 | 3000 | 0.4845 | 27.1198 |
| 0.0002 | 18.4332 | 4000 | 0.4936 | 26.9117 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1
- Datasets 3.1.0
- Tokenizers 0.20.1