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End of training
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---
language:
- so
license: apache-2.0
base_model: steja/whisper-small-somali
tags:
- generated_from_trainer
datasets:
- google/fleurs
metrics:
- wer
model-index:
- name: Whisper Small So - kheder yusuf
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: google/fleurs
type: google/fleurs
config: so_so
split: None
args: 'config: so_so, split: test'
metrics:
- name: Wer
type: wer
value: 21.001297668382936
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Whisper Small So - kheder yusuf
This model is a fine-tuned version of [steja/whisper-small-somali](https://huggingface.co/steja/whisper-small-somali) on the google/fleurs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2840
- Wer: 21.0013
## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.257 | 3.47 | 1000 | 0.2840 | 21.0013 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2