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---
language:
- fr
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- gigant/african_accented_french
metrics:
- wer
model-index:
- name: Whisper tiny Fr - Dimi3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: African accented french
type: gigant/african_accented_french
config: fr
split: None
args: fr
metrics:
- name: Wer
type: wer
value: 121.30115424973766
---
<!-- 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 tiny Fr - Dimi3
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the African accented french dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9985
- Wer: 121.3012
## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7444 | 1.0 | 587 | 0.9985 | 121.3012 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.1.2
- Datasets 2.19.2
- Tokenizers 0.19.1
|