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---
library_name: transformers
language:
- ha
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- Seon25/common_voice_16_0_
metrics:
- wer
model-index:
- name: Whisper Small Ha - Eldad Akhaumere
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.0
type: Seon25/common_voice_16_0_
config: ha
split: None
args: 'config: ha, split: test'
metrics:
- name: Wer
type: wer
value: 108.10546875
---
<!-- 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 Ha - Eldad Akhaumere
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 4.9575
- Wer Ortho: 110.3468
- Wer: 108.1055
## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- num_epochs: 13.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:--------:|
| 1.5785 | 3.1847 | 500 | 3.8839 | 99.5593 | 99.8438 |
| 1.1623 | 6.3694 | 1000 | 4.4847 | 97.7582 | 98.0078 |
| 0.9893 | 9.5541 | 1500 | 4.7922 | 108.7373 | 107.6172 |
| 0.8816 | 12.7389 | 2000 | 4.9575 | 110.3468 | 108.1055 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
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