whisper-small-ar / README.md
raghadalghonaim's picture
End of training
714d2cf verified
---
library_name: transformers
language:
- ar
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- raghadalghonaim/tts_arabic
metrics:
- wer
model-index:
- name: whisper_small_ar_ralghonaim
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: My Own Arabic DS
type: raghadalghonaim/tts_arabic
config: default
split: None
args: 'config: ar, split: test'
metrics:
- name: Wer
type: wer
value: 42.69371737440302
---
<!-- 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. -->
# whisper_small_ar_ralghonaim
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the My Own Arabic DS dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5957
- Wer: 42.6937
## 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: 16
- 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: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.6446 | 0.9268 | 1000 | 0.6416 | 48.7542 |
| 0.4115 | 1.8536 | 2000 | 0.5765 | 44.4449 |
| 0.2475 | 2.7804 | 3000 | 0.5745 | 43.3860 |
| 0.1478 | 3.7071 | 4000 | 0.5957 | 42.6937 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1