---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: local_fr
  results: []
---

<!-- 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. -->

# local_fr

This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4986
- Model Preparation Time: 0.0006
- Wer: 75.0

## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Wer  |
|:-------------:|:-----:|:----:|:---------------:|:----------------------:|:----:|
| 1.9152        | 5.0   | 5    | 2.4986          | 0.0006                 | 75.0 |
| 1.7317        | 10.0  | 10   | 2.4449          | 0.0006                 | 75.0 |
| 1.4026        | 15.0  | 15   | 2.3783          | 0.0006                 | 85.0 |
| 1.0429        | 20.0  | 20   | 2.3206          | 0.0006                 | 90.0 |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.20.3