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---
language:
- ar
license: apache-2.0
datasets:
- mozilla-foundation/common_voice_13_0
metrics:
- wer
pipeline_tag: automatic-speech-recognition
base_model: openai/whisper-small
model-index:
- name: whisper_small_hi_flax
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 13.0
type: mozilla-foundation/common_voice_13_0
config: hi
split: test
metrics:
- type: wer
value: 33.96828
name: Wer
---
# Whisper Small Hi - Sanchit Gandhi
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 13.0 dataset in Flax.
It is trained using the Transformers **Flax** examples script, and achieves the following results on the evaluation set:
- Loss: 0.02091
- Wer: 33.96828
The training run can be reproduced in approximately 25 minutes by executing the script [`run.sh`](https://huggingface.co/sanchit-gandhi/whisper-small-hi-flax/blob/main/run.sh).
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-04
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_train_epochs: 10
### Training results
See [Tensorboard logs](https://huggingface.co/sanchit-gandhi/whisper-small-hi-flax/tensorboard) for details.
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