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---
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
- hf-asr-leaderboard
datasets:
- arbml/mgb2
metrics:
- wer
model-index:
- name: Whisper Small ar - Mohammad AlMarzouq
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: mozilla-foundation/common_voice_11_0
type: mozilla-foundation/common_voice_11_0
config: ar
split: test
args: ar
metrics:
- name: Wer
type: wer
value: 43.14
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/fleurs
type: google/fleurs
config: ar_eg
split: test
args: ar
metrics:
- name: Wer
type: wer
value: 16.69
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# openai/whisper-small
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9750
- Wer: 21.3693
## 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: 64
- eval_batch_size: 8
- 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: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.3559 | 0.1 | 1000 | 0.9147 | 29.3252 |
| 0.3154 | 0.2 | 2000 | 1.1353 | 26.5718 |
| 0.359 | 0.3 | 3000 | 0.9208 | 25.3987 |
| 0.273 | 0.4 | 4000 | 0.9591 | 24.3877 |
| 0.2326 | 0.5 | 5000 | 0.9207 | 21.9052 |
| 0.2992 | 1.04 | 6000 | 0.9445 | 22.4556 |
| 0.2265 | 1.14 | 7000 | 0.9660 | 21.2230 |
| 0.2059 | 1.24 | 8000 | 0.9785 | 20.9551 |
| 0.2239 | 1.34 | 9000 | 0.9637 | 21.6300 |
| 0.2163 | 1.44 | 10000 | 0.9750 | 21.3693 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
|