---
library_name: transformers
language:
- es
license: apache-2.0
base_model: openai/whisper-large
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper openai-whisper-large
  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 openai-whisper-large

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the llamadas ecu911 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1954
- Wer: 40.5791

## 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: 2
- eval_batch_size: 1
- 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: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer     |
|:-------------:|:-------:|:----:|:---------------:|:-------:|
| 0.3338        | 2.6596  | 500  | 0.7921          | 42.5161 |
| 0.0335        | 5.3191  | 1000 | 0.9873          | 40.2465 |
| 0.0083        | 7.9787  | 1500 | 1.1470          | 40.3639 |
| 0.0007        | 10.6383 | 2000 | 1.1954          | 40.5791 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1