metadata
language:
- it
license: apache-2.0
tags:
- generated_from_trainer
- whisper-event
datasets:
- common_voice_11_0
metrics:
- wer
model-index:
- name: luigisaetta/whisper-medium-it
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_11_0
type: common_voice_11_0
config: it
split: test
args: it
metrics:
- name: Wer
type: wer
value: 5.719088879438656
luigisaetta/whisper-medium
This model is a fine-tuned version of openai/whisper-medium on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1452
- Wer: 5.7191
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 16
- 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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.1216 | 0.2 | 1000 | 0.2289 | 10.0594 |
| 0.1801 | 0.4 | 2000 | 0.1851 | 7.6593 |
| 0.1763 | 0.6 | 3000 | 0.1615 | 6.5258 |
| 0.1337 | 0.8 | 4000 | 0.1506 | 6.0427 |
| 0.0742 | 1.05 | 5000 | 0.1452 | 5.7191 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2