---
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-tiny-basque
  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. -->

# whisper-tiny-basque

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: 0.4296
- Wer: 28.7020

## 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: 256
- eval_batch_size: 128
- 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: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.7245        | 0.21  | 500   | 0.9431          | 64.8287 |
| 0.4752        | 0.42  | 1000  | 0.6923          | 48.8196 |
| 0.4115        | 0.63  | 1500  | 0.6084          | 40.8976 |
| 0.3696        | 0.84  | 2000  | 0.5597          | 37.1048 |
| 0.3336        | 1.05  | 2500  | 0.5289          | 36.0029 |
| 0.3189        | 1.26  | 3000  | 0.5082          | 33.5204 |
| 0.3007        | 1.47  | 3500  | 0.4903          | 32.4969 |
| 0.2935        | 1.68  | 4000  | 0.4802          | 31.6632 |
| 0.2839        | 1.89  | 4500  | 0.4695          | 30.7243 |
| 0.2594        | 2.1   | 5000  | 0.4615          | 30.2538 |
| 0.2507        | 2.31  | 5500  | 0.4547          | 29.4160 |
| 0.2574        | 2.52  | 6000  | 0.4487          | 29.5852 |
| 0.2523        | 2.73  | 6500  | 0.4429          | 28.5473 |
| 0.2471        | 2.94  | 7000  | 0.4393          | 29.3562 |
| 0.2329        | 3.15  | 7500  | 0.4373          | 29.2592 |
| 0.2346        | 3.36  | 8000  | 0.4343          | 28.5947 |
| 0.2322        | 3.57  | 8500  | 0.4332          | 29.0136 |
| 0.2304        | 3.78  | 9000  | 0.4305          | 28.1387 |
| 0.2299        | 3.99  | 9500  | 0.4300          | 28.0768 |
| 0.236         | 4.2   | 10000 | 0.4296          | 28.7020 |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.1.1+cu121
- Datasets 2.8.0
- Tokenizers 0.15.2