---
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: sft-llava-1.5-7b_new
  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. -->

# sft-llava-1.5-7b_new

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: 1.9504
- Bleu: 0.1425
- Rouge1: 0.4583
- Rouge2: 0.1850
- Rougel: 0.3579
- Bertscore Precision: 0.6782
- Bertscore Recall: 0.7679
- Bertscore F1: 0.7201

## 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: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Bleu   | Rouge1 | Rouge2 | Rougel | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:------:|:-------------------:|:----------------:|:------------:|
| 1.9977        | 0.9922 | 80   | 1.9963          | 0.1395 | 0.4530 | 0.1844 | 0.3520 | 0.6764              | 0.7670           | 0.7188       |
| 1.9336        | 1.9845 | 160  | 1.9504          | 0.1425 | 0.4583 | 0.1850 | 0.3579 | 0.6782              | 0.7679           | 0.7201       |


### Framework versions

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