transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer base_model:openai/whisper-small license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-small-canario_orto
  results: []
---

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# whisper-small-canario_orto

This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.4499
- Wer: 91.6524

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1319        | 5.38  | 1000 | 0.9796          | 89.6131 |
| 0.0373        | 10.75 | 2000 | 1.2377          | 90.0133 |
| 0.0213        | 16.13 | 3000 | 1.4101          | 92.6434 |
| 0.0133        | 21.51 | 4000 | 1.4499          | 91.6524 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Tokenizers 0.15.0
