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---
license: apache-2.0
base_model: mayssakorbi/whisper-tiny-ar2
tags:
- generated_from_trainer
datasets:
- common_voice_16_1
metrics:
- wer
model-index:
- name: whisper-tiny-ar2
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_16_1
type: common_voice_16_1
config: ar
split: test[1000:1500]
args: ar
metrics:
- name: Wer
type: wer
value: 87.11256117455139
---
<!-- 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-tiny-ar2
This model is a fine-tuned version of [mayssakorbi/whisper-tiny-ar2](https://huggingface.co./mayssakorbi/whisper-tiny-ar2) on the common_voice_16_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9240
- Wer Ortho: 77.8656
- Wer: 87.1126
## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 10
- training_steps: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
| 0.5216 | 0.4 | 50 | 0.9240 | 77.8656 | 87.1126 |
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|