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

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2281
- Wer: 11.8969

## 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: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 512
- total_eval_batch_size: 64
- 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.1763        | 0.42  | 500  | 0.2915          | 17.9244 |
| 0.1415        | 0.84  | 1000 | 0.2468          | 15.0738 |
| 0.1182        | 1.26  | 1500 | 0.2483          | 14.3144 |
| 0.1234        | 1.68  | 2000 | 0.2520          | 14.1380 |
| 0.0961        | 2.1   | 2500 | 0.2397          | 13.6557 |
| 0.0952        | 2.52  | 3000 | 0.2360          | 12.7999 |
| 0.0912        | 2.94  | 3500 | 0.2264          | 12.4284 |
| 0.0717        | 3.36  | 4000 | 0.2295          | 12.0590 |
| 0.0698        | 3.78  | 4500 | 0.2260          | 12.2581 |
| 0.0582        | 4.2   | 5000 | 0.2281          | 11.8969 |


### Framework versions

- Transformers 4.38.0
- Pytorch 2.1.1+cu121
- Datasets 2.8.0
- Tokenizers 0.15.2