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---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- tachelhit_darija
metrics:
- wer
model-index:
- name: whisper-small-darija
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: tachelhit_darija
type: tachelhit_darija
config: default
split: None
args: default
metrics:
- type: wer
value: 27.93522267206478
name: Wer
---
<!-- 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-darija
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the tachelhit_darija dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3828
- Wer: 27.9352
## 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: 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: 100
- training_steps: 1000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.572 | 1.4286 | 100 | 0.6403 | 60.7287 |
| 0.2156 | 2.8571 | 200 | 0.4233 | 42.7800 |
| 0.0459 | 4.2857 | 300 | 0.3953 | 48.1781 |
| 0.0257 | 5.7143 | 400 | 0.3663 | 31.0391 |
| 0.0089 | 7.1429 | 500 | 0.3857 | 31.9838 |
| 0.0029 | 8.5714 | 600 | 0.3748 | 30.3644 |
| 0.0026 | 10.0 | 700 | 0.3756 | 29.4197 |
| 0.0012 | 11.4286 | 800 | 0.3801 | 27.5304 |
| 0.0011 | 12.8571 | 900 | 0.3821 | 27.9352 |
| 0.0013 | 14.2857 | 1000 | 0.3828 | 27.9352 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
|