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---
language:
- nyn
license: apache-2.0
base_model: openai/whisper-small
tags:
- whisper-event
- generated_from_trainer
datasets:
- tericlabs
metrics:
- wer
model-index:
- name: Whisper Small Runyankore
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Yogera data
type: tericlabs
config: nyn
split: test
args: nyn
metrics:
- name: Wer
type: wer
value: 96.9176052163604
---
<!-- 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 Runyankore
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Yogera data dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6289
- Wer: 96.9176
## 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: 8
- 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: 300
- training_steps: 200
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.9225 | 0.5 | 100 | 2.3983 | 126.6153 |
| 1.8681 | 1.25 | 200 | 1.6289 | 96.9176 |
### Framework versions
- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
|