metadata
language:
- it
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
model-index:
- name: Whisper Medium Italian - Robust
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_11_0 it
type: mozilla-foundation/common_voice_11_0
config: it
split: train
args: it
metrics:
- type: wer
value: 7.651366149266425
name: Wer
- type: wer
value: 6.6
name: WER
Whisper Medium Italian - Robust
This model is a fine-tuned version of openai/whisper-medium on the mozilla-foundation/common_voice_11_0 it dataset. It achieves the following results on the evaluation set:
- Loss: 0.1388
- WER (Augmented Test): 7.65
IMPORTANT The model has been trained using data augmentation to improve its generalization capabilities and robustness. The results on the eval set during training are biased towards data augmentation applied to evaluation data.
Results on eval set
- Mozilla CV 11.0 - Italian: 6.60 WER (using official script)
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: 5e-05
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 7500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.226 | 0.33 | 2500 | 0.2779 | 14.6642 |
| 0.1278 | 1.03 | 5000 | 0.1818 | 10.2049 |
| 0.0304 | 1.36 | 7500 | 0.1388 | 7.5544 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2