metadata
library_name: peft
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-model-small-ro-finetune-5k-50-50
results: []
whisper-model-small-ro-finetune-5k-50-50
This model is a fine-tuned version of openai/whisper-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.0462
- Wer: 0.2851
- Cer: 0.0710
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 30
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 2.5278 | 1.0 | 125 | 1.3356 | 0.7715 | 0.8917 |
| 1.5011 | 2.0 | 250 | 1.1585 | 0.5180 | 0.3362 |
| 1.4233 | 3.0 | 375 | 1.0967 | 0.3243 | 0.1098 |
| 1.3585 | 4.0 | 500 | 1.0608 | 0.2867 | 0.0722 |
| 1.3203 | 5.0 | 625 | 1.0462 | 0.2851 | 0.0710 |
Framework versions
- PEFT 0.15.2
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1