metadata
license: apache-2.0
base_model: arun100/whisper-base-ar-1
tags:
- whisper-event
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Base Arabic Derived
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/fleurs ar_eg
type: google/fleurs
config: ar_eg
split: test
args: ar_eg
metrics:
- name: Wer
type: wer
value: 44.287968920723564
Whisper Base Arabic Derived
This model is a fine-tuned version of arun100/whisper-base-ar-1 on the google/fleurs ar_eg dataset. It achieves the following results on the evaluation set:
- Loss: 0.6670
- Wer: 44.2880
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: 5e-07
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5692 | 52.63 | 500 | 0.6253 | 54.7894 |
| 0.3447 | 105.26 | 1000 | 0.6001 | 45.2106 |
| 0.2067 | 157.89 | 1500 | 0.6109 | 44.7372 |
| 0.1273 | 210.53 | 2000 | 0.6303 | 44.7372 |
| 0.0788 | 263.16 | 2500 | 0.6508 | 44.4579 |
| 0.0526 | 315.79 | 3000 | 0.6670 | 44.2880 |
| 0.0404 | 368.42 | 3500 | 0.6784 | 44.7129 |
| 0.0335 | 421.05 | 4000 | 0.6860 | 46.2668 |
| 0.0296 | 473.68 | 4500 | 0.6907 | 44.5915 |
| 0.0287 | 526.32 | 5000 | 0.6924 | 44.6279 |
Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.2.dev0
- Tokenizers 0.15.0