metadata
base_model: openai/whisper-medium
datasets:
- facebook/voxpopuli
language:
- it
library_name: peft
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: Whisper Medium
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: facebook/voxpopuli
type: facebook/voxpopuli
config: default
split: None
args: default
metrics:
- type: wer
value: 10.9375
name: Wer
Whisper Medium
This model is a fine-tuned version of openai/whisper-medium on the facebook/voxpopuli dataset. It achieves the following results on the evaluation set:
- Loss: 0.4874
- Wer: 10.9375
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 1200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.2174 | 0.5714 | 100 | 1.9102 | 49.4792 |
| 0.2353 | 1.1429 | 200 | 0.3485 | 30.7292 |
| 0.1668 | 1.7143 | 300 | 0.7634 | 21.875 |
| 0.118 | 2.2857 | 400 | 0.6914 | 11.9792 |
| 0.0931 | 2.8571 | 500 | 0.5523 | 15.1042 |
| 0.0851 | 3.4286 | 600 | 0.6818 | 13.0208 |
| 0.0751 | 4.0 | 700 | 0.6348 | 11.9792 |
| 0.066 | 4.5714 | 800 | 0.6576 | 11.9792 |
| 0.0604 | 5.1429 | 900 | 0.4125 | 10.9375 |
| 0.0564 | 5.7143 | 1000 | 0.6815 | 10.9375 |
| 0.0499 | 6.2857 | 1100 | 0.4861 | 11.4583 |
| 0.0472 | 6.8571 | 1200 | 0.4874 | 10.9375 |
Framework versions
- PEFT 0.12.0
- Transformers 4.43.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1