---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
datasets:
- common_voice_11_0
base_model: openai/whisper-large-v2
model-index:
- name: openai-whisper-large-v2-LORA-colab
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# openai-whisper-large-v2-LORA-colab

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the common_voice_11_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1374

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.1865        | 1.0   | 1410 | 0.1704          |
| 0.0955        | 2.0   | 2820 | 0.1426          |
| 0.0165        | 3.0   | 4230 | 0.1374          |


### Framework versions

- PEFT 0.8.2
- Transformers 4.39.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.1.dev0
- Tokenizers 0.15.1