---
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-hf3
  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-hf3

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: 13.1181
- Bleu: 0.0
- Rouge1: 0.0651
- Rouge2: 0.0043
- Rougel: 0.0508
- Bertscore Precision: 0.6243
- Bertscore Recall: 0.7482
- Bertscore F1: 0.6806

## 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 |
|:-------------:|:------:|:----:|:---------------:|:----:|:------:|:------:|:------:|:-------------------:|:----------------:|:------------:|
| 6.903         | 0.3101 | 200  | 22.1793         | 0.0  | 0.0440 | 0.0    | 0.0441 | 0.6243              | 0.7482           | 0.6806       |
| 6.585         | 0.6202 | 400  | 27.3559         | 0.0  | 0.0546 | 0.0043 | 0.0425 | 0.6243              | 0.7482           | 0.6806       |
| 6.5197        | 0.9302 | 600  | 26.1987         | 0.0  | 0.0546 | 0.0043 | 0.0425 | 0.6243              | 0.7482           | 0.6806       |
| 6.2662        | 1.2403 | 800  | 21.1666         | 0.0  | 0.0633 | 0.0043 | 0.0520 | 0.6243              | 0.7482           | 0.6806       |
| 6.0303        | 1.5504 | 1000 | 21.0359         | 0.0  | 0.0651 | 0.0043 | 0.0508 | 0.6243              | 0.7482           | 0.6806       |
| 5.7602        | 1.8605 | 1200 | 19.0201         | 0.0  | 0.0651 | 0.0043 | 0.0508 | 0.6243              | 0.7482           | 0.6806       |
| 5.6359        | 2.1705 | 1400 | 18.6311         | 0.0  | 0.0651 | 0.0043 | 0.0508 | 0.6243              | 0.7482           | 0.6806       |
| 5.5176        | 2.4806 | 1600 | 17.9442         | 0.0  | 0.0649 | 0.0043 | 0.0496 | 0.6243              | 0.7482           | 0.6806       |
| 5.4608        | 2.7907 | 1800 | 16.6921         | 0.0  | 0.0651 | 0.0043 | 0.0508 | 0.6243              | 0.7482           | 0.6806       |
| 5.2881        | 3.1008 | 2000 | 15.3415         | 0.0  | 0.0651 | 0.0043 | 0.0508 | 0.6243              | 0.7482           | 0.6806       |
| 5.2429        | 3.4109 | 2200 | 14.8475         | 0.0  | 0.0651 | 0.0043 | 0.0508 | 0.6243              | 0.7482           | 0.6806       |
| 5.1929        | 3.7209 | 2400 | 14.2828         | 0.0  | 0.0651 | 0.0043 | 0.0508 | 0.6243              | 0.7482           | 0.6806       |
| 5.1259        | 4.0310 | 2600 | 13.8075         | 0.0  | 0.0651 | 0.0043 | 0.0508 | 0.6243              | 0.7482           | 0.6806       |
| 5.0379        | 4.3411 | 2800 | 13.4751         | 0.0  | 0.0651 | 0.0043 | 0.0508 | 0.6243              | 0.7482           | 0.6806       |
| 5.1071        | 4.6512 | 3000 | 13.2275         | 0.0  | 0.0651 | 0.0043 | 0.0508 | 0.6243              | 0.7482           | 0.6806       |
| 5.1082        | 4.9612 | 3200 | 13.1181         | 0.0  | 0.0651 | 0.0043 | 0.0508 | 0.6243              | 0.7482           | 0.6806       |


### Framework versions

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