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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: openai/whisper-small
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: ar
split: test
args: ar
metrics:
- name: Wer
type: wer
value: 44.976586
---
<!-- 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 common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.322550
- Wer: 44.976586
## 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:
train_batch_size=16
gradient_accumulation_steps=1
learning_rate=1e-5
warmup_steps=500
max_steps=4000
gradient_checkpointing=True
fp16=True
evaluation_strategy="steps"
save_steps=1000
eval_steps=1000
logging_steps=25
metric_for_best_model="wer"
### Training results
| Training Loss | Step | Validation Loss | Wer |
|:-------------:|:----:|:----------------:|:---------:|
| 0.2811 | 1000 | 0.393018 | 53.778349 |
| 0.2356 | 2000 | 0.348794 | 47.793591 |
| 0.1705 | 3000 | 0.332207 | 45.758883 |
| 0.1476 | 4000 | 0.322550 | 44.976586 |
### Framework versions
|