---
base_model: openai/whisper-large
language:
- es
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: Whisper openai-whisper-large-LoRA32-es_ecu911
  results: []
---

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# Whisper openai-whisper-large-LoRA32-es_ecu911

This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the llamadas ecu9111 segmentos dmarquez dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7446

## 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: 0.0002
- train_batch_size: 8
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.253         | 1.0   | 53   | 1.0113          |
| 0.7443        | 2.0   | 106  | 0.7473          |
| 0.6761        | 3.0   | 159  | 0.7312          |
| 0.6156        | 4.0   | 212  | 0.7381          |
| 0.5384        | 5.0   | 265  | 0.7446          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1