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# Whisper Small IT

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5372
- Wer: 130.3266

## 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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1972        | 1.6   | 500  | 0.4266          | 105.1927 |
| 0.033         | 3.19  | 1000 | 0.4507          | 209.0820 |
| 0.0167        | 4.79  | 1500 | 0.4738          | 96.0643  |
| 0.0052        | 6.39  | 2000 | 0.4948          | 143.7616 |
| 0.0035        | 7.99  | 2500 | 0.5144          | 126.8133 |
| 0.0047        | 9.58  | 3000 | 0.5273          | 133.8966 |
| 0.0033        | 11.18 | 3500 | 0.5349          | 137.8580 |
| 0.0026        | 12.78 | 4000 | 0.5372          | 130.3266 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0

{"language": ["it"], "license": "apache-2.0", "tags": ["hf-asr-leaderboard", "generated_from_trainer"], "metrics": ["wer"], "base_model": "openai/whisper-small", "model-index": [{"name": "Whisper Small IT", "results": []}]}
transformers tensorboard safetensors whisper automatic-speech-recognition hf-asr-leaderboard generated_from_trainer it base_model:openai/whisper-small license:apache-2.0 endpoints_compatible has_space region:us