metadata
library_name: transformers
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- abdouaziiz/fulfulde_lam
metrics:
- wer
model-index:
- name: whisper-medium-v3-ff4
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: abdouaziiz/fulfulde_lam
type: abdouaziiz/fulfulde_lam
metrics:
- name: Wer
type: wer
value: 0.16938691239432335
whisper-medium-v3-ff4
This model is a fine-tuned version of openai/whisper-small on the abdouaziiz/fulfulde_lam dataset. It achieves the following results on the evaluation set:
- Loss: 0.2572
- Wer: 0.1694
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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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: 50
- training_steps: 26000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3543 | 0.6393 | 5000 | 0.3380 | 0.2361 |
| 0.2259 | 1.2786 | 10000 | 0.2893 | 0.2022 |
| 0.1938 | 1.9179 | 15000 | 0.2597 | 0.1790 |
| 0.1119 | 2.5572 | 20000 | 0.2572 | 0.1694 |
| 0.0632 | 3.1965 | 25000 | 0.2615 | 0.1660 |
Framework versions
- Transformers 4.46.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.20.3