library_name, language, license, base_model, tags, datasets, metrics, model-index
| library_name |
language |
license |
base_model |
tags |
datasets |
metrics |
model-index |
| transformers |
|
apache-2.0 |
openai/whisper-small |
|
| mozilla-foundation/common_voice_4_0 |
|
|
| name |
results |
| whisper-small-italian-tuned |
| task |
dataset |
metrics |
| name |
type |
| Automatic Speech Recognition |
automatic-speech-recognition |
|
| name |
type |
config |
split |
args |
| Common Voice 4.0 |
mozilla-foundation/common_voice_4_0 |
it |
test |
config: it, split: test |
|
| name |
type |
value |
| Wer |
wer |
20.230225666742648 |
|
|
|
|
|
|
whisper-small-italian-tuned
This model is a fine-tuned version of openai/whisper-small on the Common Voice 4.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2653
- Wer: 20.2302
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: 16
- 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: 300
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss |
Epoch |
Step |
Validation Loss |
Wer |
| 0.2668 |
0.5647 |
1000 |
0.3023 |
22.8539 |
| 0.1314 |
1.1293 |
2000 |
0.2735 |
20.6998 |
| 0.118 |
1.6940 |
3000 |
0.2648 |
20.4263 |
| 0.0644 |
2.2586 |
4000 |
0.2653 |
20.2302 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 2.21.0
- Tokenizers 0.20.3
