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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- common_voice_22_0
metrics:
- wer
model-index:
- name: openai/whisper-small
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_22_0
type: common_voice_22_0
config: eu
split: test
args: eu
metrics:
- name: Wer
type: wer
value: 12.160220434106431
---
<!-- 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_22_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3891
- Wer: 12.1602
## 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: 3.75e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 100000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:--------:|:-----:|:---------------:|:-------:|
| 0.0113 | 10.8225 | 5000 | 0.2778 | 12.1163 |
| 0.0047 | 21.6450 | 10000 | 0.3096 | 11.8923 |
| 0.0059 | 32.4675 | 15000 | 0.3285 | 12.1856 |
| 0.0028 | 43.2900 | 20000 | 0.3573 | 11.6886 |
| 0.0015 | 54.1126 | 25000 | 0.3549 | 11.6117 |
| 0.0028 | 64.9351 | 30000 | 0.3610 | 11.9312 |
| 0.0013 | 75.7576 | 35000 | 0.3711 | 11.6683 |
| 0.0009 | 86.5801 | 40000 | 0.3756 | 11.6176 |
| 0.0008 | 97.4026 | 45000 | 0.3801 | 11.8213 |
| 0.0009 | 108.2251 | 50000 | 0.3891 | 12.1602 |
### Framework versions
- Transformers 4.52.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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