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

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llava_test

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: 2.5219
- Bleu: 0.0477
- Rouge1: 0.2804
- Rouge2: 0.0966
- Rougel: 0.2140
- Bertscore Precision: 0.7005
- Bertscore Recall: 0.7759
- Bertscore F1: 0.7362

## 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
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Bleu   | Rouge1 | Rouge2 | Rougel | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:-------------------:|:----------------:|:------------:|
| 0.3261        | 10.0  | 10   | 2.5219          | 0.0477 | 0.2804 | 0.0966 | 0.2140 | 0.7005              | 0.7759           | 0.7362       |


### Framework versions

- PEFT 0.13.0
- Transformers 4.45.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.20.1