---
base_model: meta-llama/Llama-3.2-11B-Vision-Instruct
library_name: peft
license: llama3.2
metrics:
- bleu
- rouge
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Llama-3.2-11B-Vision-Instruct
  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. -->

# Llama-3.2-11B-Vision-Instruct

This model is a fine-tuned version of [meta-llama/Llama-3.2-11B-Vision-Instruct](https://huggingface.co./meta-llama/Llama-3.2-11B-Vision-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7115
- Bleu: 0.3191
- Rouge1: 0.6462
- Rouge2: 0.3482
- Rougel: 0.5529
- Bertscore Precision: 0.8764
- Bertscore Recall: 0.8935
- Bertscore F1: 0.8848

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Bleu   | Rouge1 | Rouge2 | Rougel | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:------:|:-------------------:|:----------------:|:------------:|
| 1.7942        | 0.6202 | 50   | 1.7909          | 0.2890 | 0.6131 | 0.3240 | 0.5197 | 0.8199              | 0.8912           | 0.8535       |
| 1.7177        | 1.2403 | 100  | 1.7262          | 0.3165 | 0.6445 | 0.3454 | 0.5501 | 0.8724              | 0.8928           | 0.8825       |
| 1.7198        | 1.8605 | 150  | 1.7158          | 0.3184 | 0.6462 | 0.3475 | 0.5520 | 0.8753              | 0.8932           | 0.8841       |
| 1.6898        | 2.4806 | 200  | 1.7115          | 0.3191 | 0.6462 | 0.3482 | 0.5529 | 0.8764              | 0.8935           | 0.8848       |


### Framework versions

- PEFT 0.13.0
- Transformers 4.45.2
- Pytorch 2.2.0a0+81ea7a4
- Datasets 3.0.1
- Tokenizers 0.20.1