metadata
base_model: openai/whisper-large-v3
datasets:
- MightyStudent/Egyptian-ASR-MGB-3
language:
- ar
library_name: peft
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: Whisper large V3 Arabic
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: MightyStudent/Egyptian-ASR-MGB-3
type: MightyStudent/Egyptian-ASR-MGB-3
metrics:
- type: wer
value: 38.095238095238095
name: Wer
Whisper large V3 Arabic
This model is a fine-tuned version of openai/whisper-large-v3 on the MightyStudent/Egyptian-ASR-MGB-3 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6890
- Wer: 38.0952
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: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.6852 | 0.2 | 10 | 0.7062 | 45.7143 |
0.7504 | 0.4 | 20 | 0.6994 | 45.7143 |
0.7219 | 0.6 | 30 | 0.6940 | 45.7143 |
0.6971 | 0.8 | 40 | 0.6905 | 45.7143 |
0.6846 | 1.0 | 50 | 0.6890 | 38.0952 |
Framework versions
- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1