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---
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 |