metadata
language:
- ar
license: apache-2.0
tags:
- ar-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
base_model: openai/whisper-medium
model-index:
- name: Whisper Medium Ar - AxAI
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Client
type: mozilla-foundation/common_voice_16_1
config: default
split: None
args: default
metrics:
- type: wer
value: 100
name: Wer
Whisper Medium Ar - AxAI
This model is a fine-tuned version of openai/whisper-medium on the Client dataset. It achieves the following results on the evaluation set:
- Loss: 3.5466
- Wer: 100.0
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: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- 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 |
|---|---|---|---|---|
| 0.0411 | 24.39 | 500 | 2.8748 | 100.0 |
| 0.0063 | 48.78 | 1000 | 3.3347 | 100.0 |
| 0.0017 | 73.17 | 1500 | 3.4076 | 100.0 |
| 0.0003 | 97.56 | 2000 | 3.4587 | 100.0 |
| 0.0001 | 121.95 | 2500 | 3.5256 | 100.0 |
| 0.0001 | 146.34 | 3000 | 3.5325 | 100.0 |
| 0.0001 | 170.73 | 3500 | 3.5419 | 100.0 |
| 0.0001 | 195.12 | 4000 | 3.5466 | 100.0 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2