---
library_name: transformers
license: llama2
base_model: llava-hf/llava-1.5-7b-hf
tags:
- trl
- sft
- generated_from_trainer
metrics:
- bleu
- rouge
model-index:
- name: sft-llava-1.5-7b_lora
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# sft-llava-1.5-7b_lora

This model is a fine-tuned version of [llava-hf/llava-1.5-7b-hf](https://huggingface.co/llava-hf/llava-1.5-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9404
- Bleu: 0.1802
- Rouge1: 0.4861
- Rouge2: 0.1709
- Rougel: 0.3580
- Bertscore Precision: 0.6578
- Bertscore Recall: 0.7479
- Bertscore F1: 0.6999

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 5.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Bleu   | Rouge1 | Rouge2 | Rougel | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:------:|:-------------------:|:----------------:|:------------:|
| 5.7514        | 0.3101 | 200  | 5.6831          | 0.0772 | 0.2028 | 0.0717 | 0.1778 | 0.6381              | 0.7437           | 0.6869       |
| 2.9737        | 0.6202 | 400  | 2.9242          | 0.1580 | 0.4319 | 0.1445 | 0.3306 | 0.6578              | 0.7479           | 0.6999       |
| 2.6756        | 0.9302 | 600  | 2.6594          | 0.1839 | 0.4859 | 0.1759 | 0.3680 | 0.6381              | 0.7437           | 0.6869       |
| 2.18          | 1.2403 | 800  | 2.5783          | 0.1754 | 0.4864 | 0.1754 | 0.3775 | 0.6578              | 0.7479           | 0.6999       |
| 2.0957        | 1.5504 | 1000 | 2.5019          | 0.1849 | 0.4877 | 0.1850 | 0.3801 | 0.6578              | 0.7479           | 0.6999       |
| 2.0109        | 1.8605 | 1200 | 2.4393          | 0.1879 | 0.4911 | 0.1840 | 0.3859 | 0.6578              | 0.7479           | 0.6999       |
| 0.7656        | 2.1705 | 1400 | 2.9613          | 0.1808 | 0.4810 | 0.1719 | 0.3644 | 0.6578              | 0.7479           | 0.6999       |
| 0.7271        | 2.4806 | 1600 | 3.0544          | 0.1817 | 0.4795 | 0.1695 | 0.3629 | 0.6578              | 0.7479           | 0.6999       |
| 0.6746        | 2.7907 | 1800 | 3.0377          | 0.1754 | 0.4765 | 0.1639 | 0.3508 | 0.6578              | 0.7479           | 0.6999       |
| 0.1183        | 3.1008 | 2000 | 3.6408          | 0.1801 | 0.4821 | 0.1710 | 0.3636 | 0.6578              | 0.7479           | 0.6999       |
| 0.1123        | 3.4109 | 2200 | 3.6913          | 0.1765 | 0.4903 | 0.1712 | 0.3629 | 0.6578              | 0.7479           | 0.6999       |
| 0.1051        | 3.7209 | 2400 | 3.7181          | 0.1766 | 0.4884 | 0.1701 | 0.3618 | 0.6578              | 0.7479           | 0.6999       |
| 0.046         | 4.0310 | 2600 | 3.7719          | 0.1781 | 0.4849 | 0.1711 | 0.3598 | 0.6578              | 0.7479           | 0.6999       |
| 0.0444        | 4.3411 | 2800 | 3.9170          | 0.1801 | 0.4852 | 0.1719 | 0.3595 | 0.6578              | 0.7479           | 0.6999       |
| 0.0452        | 4.6512 | 3000 | 3.9377          | 0.1808 | 0.4872 | 0.1714 | 0.3604 | 0.6578              | 0.7479           | 0.6999       |
| 0.0449        | 4.9612 | 3200 | 3.9404          | 0.1802 | 0.4861 | 0.1709 | 0.3580 | 0.6578              | 0.7479           | 0.6999       |


### Framework versions

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