metadata
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Small ar - younes matrab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: ar
split: None
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 61.65413533834586
Whisper Small ar - younes matrab
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.8027
- Wer: 61.6541
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 4
- 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: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 1.7188 | 0.4167 | 10 | 2.7773 | 67.1053 |
| 1.6979 | 0.8333 | 20 | 2.4033 | 66.5414 |
| 1.3932 | 1.25 | 30 | 1.9422 | 66.3534 |
| 1.0467 | 1.6667 | 40 | 1.6225 | 65.2256 |
| 0.8824 | 2.0833 | 50 | 1.3586 | 64.4737 |
| 0.5935 | 2.5 | 60 | 1.0915 | 62.4060 |
| 0.4491 | 2.9167 | 70 | 0.8986 | 63.3459 |
| 0.3438 | 3.3333 | 80 | 0.8473 | 61.6541 |
| 0.2915 | 3.75 | 90 | 0.8132 | 60.1504 |
| 0.2391 | 4.1667 | 100 | 0.8027 | 61.6541 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1