---
library_name: transformers
license: gemma
base_model: vidore/colpaligemma-3b-pt-448-base
tags:
- colpali
- generated_from_trainer
model-index:
- name: finetune_colpali_v1_2-olje_norsk-4bit
  results: []
---

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# finetune_colpali_v1_2-olje_norsk-4bit

This model is a fine-tuned version of [vidore/colpaligemma-3b-pt-448-base](https://huggingface.co/vidore/colpaligemma-3b-pt-448-base) on the ynuwara/norsk-olje-gass-QnA-ColPali dataset.

## Model description

ColPaliGemma-3B model is fine-tuned on a specific question and answering dataset from a book about Oil and Gas in Norwegian language. Fine tuning is done on Colab Pro's NVIDIA A100 GPU.

## Intended uses & limitations

This model is suited for RAG uses in oil and gas domain, specifically if the query is in Norwegian

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 1.5

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.0833 | 1    | 0.0837          |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3