metadata
language:
- it
license: apache-2.0
tags:
- whisper-event
- generated_from_trainer
base_model: openai/whisper-medium
datasets:
- mozilla-foundation/common_voice_17_0
- google/fleurs
- facebook/multilingual_librispeech
- facebook/voxpopuli
metrics:
- wer
model-index:
- name: Whisper Medium Mixed-Italian
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: mozilla-foundation/common_voice_17_0 it
type: mozilla-foundation/common_voice_17_0
config: it
split: test
args: it
metrics:
- type: wer
value: 6.840122206312234
name: Wer
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: google/fleurs
type: google/fleurs
config: it_it
split: test
metrics:
- type: wer
value: 3.75
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: facebook/multilingual_librispeech
type: facebook/multilingual_librispeech
config: italian
split: test
metrics:
- type: wer
value: 11.44
name: WER
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: facebook/voxpopuli
type: facebook/voxpopuli
config: it
split: test
metrics:
- type: wer
value: 17.94
name: WER
pipeline_tag: automatic-speech-recognition
Whisper Medium Mixed-Italian
This model is a fine-tuned version of openai/whisper-medium on the it datasets:
- mozilla-foundation/common_voice_17_0
- google/fleurs
- facebook/multilingual_librispeech
- facebook/voxpopuli
It achieves the following results on the evaluation set:
- Loss: 0.1318
- Wer: 6.8401
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: 8
- 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 |
|---|---|---|---|---|
| 0.1502 | 0.2 | 1000 | 0.1708 | 9.0922 |
| 0.1584 | 0.4 | 2000 | 0.1554 | 8.1757 |
| 0.1309 | 0.6 | 3000 | 0.1426 | 7.4142 |
| 0.0984 | 0.8 | 4000 | 0.1370 | 7.1298 |
| 0.0933 | 1.0 | 5000 | 0.1318 | 6.8401 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1