metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-large-v2-arabic-24h
results: []
whisper-large-v2-arabic-24h
This model is a fine-tuned version of openai/whisper-large-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3434
- Wer: 0.4239
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: 50
- eval_batch_size: 16
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1638 | 1.78 | 1000 | 0.2295 | 0.4410 |
| 0.0587 | 3.57 | 2000 | 0.2337 | 0.4272 |
| 0.0125 | 5.35 | 3000 | 0.2745 | 0.4208 |
| 0.004 | 7.13 | 4000 | 0.3124 | 0.4252 |
| 0.0016 | 8.91 | 5000 | 0.3434 | 0.4239 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.1
- Datasets 2.8.1.dev0
- Tokenizers 0.13.2