metadata
library_name: peft
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
- generated_from_trainer
model-index:
- name: whisper-large-v3-mn-ft
results: []
whisper-large-v3-mn-ft
This model is a fine-tuned version of openai/whisper-large-v3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5429
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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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: 500
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.4317 | 0.5903 | 500 | 0.7475 |
| 1.1836 | 1.1806 | 1000 | 0.5816 |
| 0.8169 | 1.7710 | 1500 | 0.5508 |
| 0.5782 | 2.3613 | 2000 | 0.5468 |
| 0.4928 | 2.9516 | 2500 | 0.5429 |
Framework versions
- PEFT 0.5.0
- Transformers 4.51.3
- Pytorch 2.7.0+cu118
- Datasets 3.5.0
- Tokenizers 0.21.1