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---
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 Small 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: test
args: it
metrics:
- name: WER
type: wer
value: 8.00
---
<!-- 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 - Robust
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_11_0 it dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1980
- Wer: 8.7457
**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: 8.00 wer (using official script)
- TODO
## 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: 25000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.1927 | 1.0 | 2500 | 0.2506 | 14.9991 |
| 0.0736 | 2.01 | 5000 | 0.2258 | 12.7864 |
| 0.0413 | 3.01 | 7500 | 0.2144 | 11.4508 |
| 0.0201 | 4.02 | 10000 | 0.2146 | 10.8774 |
| 0.0129 | 5.02 | 12500 | 0.2127 | 10.6920 |
| 0.0091 | 6.03 | 15000 | 0.2117 | 10.2867 |
| 0.0043 | 7.03 | 17500 | 0.2076 | 9.6860 |
| 0.0018 | 8.04 | 20000 | 0.2065 | 9.4235 |
| 0.0013 | 9.04 | 22500 | 0.2003 | 8.9105 |
| 0.0009 | 10.05 | 25000 | 0.1978 | 8.7497 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
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