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---
base_model: openai/whisper-small
datasets:
- mozilla-foundation/common_voice_17_0
- google/fleurs
- facebook/multilingual_librispeech
language:
- it
license: apache-2.0
metrics:
- wer
tags:
- whisper-event
- generated_from_trainer
model-index:
- name: Whisper Small 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: 10.587474512857398
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: 25.87
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 Small Mixed-Italian
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the mozilla-foundation/common_voice_17_0 it dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1909
- Wer: 10.5875
## 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: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.2213 | 0.2 | 1000 | 0.2407 | 13.4605 |
| 0.1582 | 0.4 | 2000 | 0.2143 | 12.2642 |
| 0.1913 | 0.6 | 3000 | 0.2022 | 11.2328 |
| 0.1538 | 0.8 | 4000 | 0.1951 | 11.1187 |
| 0.1286 | 1.0 | 5000 | 0.1909 | 10.5875 |
### Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |