84 lines
2.0 KiB
Markdown
84 lines
2.0 KiB
Markdown
---
|
|
library_name: transformers
|
|
language:
|
|
- it
|
|
license: apache-2.0
|
|
base_model: openai/whisper-small
|
|
tags:
|
|
- generated_from_trainer
|
|
datasets:
|
|
- mozilla-foundation/common_voice_4_0
|
|
metrics:
|
|
- wer
|
|
model-index:
|
|
- name: whisper-small-italian-tuned
|
|
results:
|
|
- task:
|
|
name: Automatic Speech Recognition
|
|
type: automatic-speech-recognition
|
|
dataset:
|
|
name: Common Voice 4.0
|
|
type: mozilla-foundation/common_voice_4_0
|
|
config: it
|
|
split: test
|
|
args: 'config: it, split: test'
|
|
metrics:
|
|
- name: Wer
|
|
type: wer
|
|
value: 20.230225666742648
|
|
---
|
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
should probably proofread and complete it, then remove this comment. -->
|
|
|
|
# whisper-small-italian-tuned
|
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/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
|