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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 Medium 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: train
args: it
metrics:
- type: wer
value: 7.651366149266425
name: Wer
- type: wer
value: 6.6
name: WER
---
<!-- 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 Medium Italian - Robust
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the mozilla-foundation/common_voice_11_0 it dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1388
- WER (Augmented Test): 7.65
**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: 6.60 WER (using official script)
## 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: 7500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.226 | 0.33 | 2500 | 0.2779 | 14.6642 |
| 0.1278 | 1.03 | 5000 | 0.1818 | 10.2049 |
| 0.0304 | 1.36 | 7500 | 0.1388 | 7.5544 |
### Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
|