---
library_name: peft
license: mit
base_model: Salesforce/blip2-opt-2.7b
tags:
- base_model:adapter:Salesforce/blip2-opt-2.7b
- lora
- transformers
model-index:
- name: blip2-lora-finetune-2
  results: []
---

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<a href="https://huggingface.co/spaces/viswakiranvvs/blip2-lora-finetune-2-trackio" target="_blank"><img src="https://raw.githubusercontent.com/gradio-app/trackio/refs/heads/main/trackio/assets/badge.png" alt="Visualize in Trackio" title="Visualize in Trackio" style="height: 40px;"/></a>
# blip2-lora-finetune-2

This model is a fine-tuned version of [Salesforce/blip2-opt-2.7b](https://huggingface.co/Salesforce/blip2-opt-2.7b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7935

## 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: 2e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.15
- num_epochs: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 102.7678      | 0.5979  | 50   | 13.0764         |
| 86.8701       | 1.1913  | 100  | 10.7530         |
| 54.3081       | 1.7892  | 150  | 6.4039          |
| 18.5161       | 2.3827  | 200  | 2.0638          |
| 9.7514        | 2.9806  | 250  | 1.1446          |
| 9.7667        | 3.5740  | 300  | 1.0239          |
| 7.3572        | 4.1674  | 350  | 0.9157          |
| 7.6331        | 4.7653  | 400  | 0.8900          |
| 7.8984        | 5.3587  | 450  | 0.8654          |
| 7.5447        | 5.9567  | 500  | 0.8642          |
| 7.2598        | 6.5501  | 550  | 0.8483          |
| 8.3937        | 7.1435  | 600  | 0.8402          |
| 6.9849        | 7.7414  | 650  | 0.8205          |
| 7.0229        | 8.3348  | 700  | 0.8303          |
| 7.4894        | 8.9327  | 750  | 0.8250          |
| 8.0766        | 9.5262  | 800  | 0.8261          |
| 6.8229        | 10.1196 | 850  | 0.8080          |
| 6.3603        | 10.7175 | 900  | 0.8184          |
| 6.8538        | 11.3109 | 950  | 0.8257          |
| 6.5484        | 11.9088 | 1000 | 0.8114          |
| 7.1385        | 12.5022 | 1050 | 0.8148          |
| 7.1053        | 13.0957 | 1100 | 0.8309          |
| 6.8619        | 13.6936 | 1150 | 0.8110          |
| 6.9226        | 14.2870 | 1200 | 0.8279          |
| 6.5827        | 14.8849 | 1250 | 0.8123          |
| 7.4853        | 15.4783 | 1300 | 0.8072          |
| 7.3401        | 16.0717 | 1350 | 0.8103          |
| 6.5739        | 16.6697 | 1400 | 0.8020          |
| 7.0551        | 17.2631 | 1450 | 0.7967          |
| 7.7921        | 17.8610 | 1500 | 0.8073          |
| 6.6075        | 18.4544 | 1550 | 0.8066          |
| 6.3661        | 19.0478 | 1600 | 0.7947          |
| 6.5013        | 19.6457 | 1650 | 0.8012          |
| 7.7917        | 20.2392 | 1700 | 0.7953          |
| 7.4042        | 20.8371 | 1750 | 0.7989          |
| 7.2549        | 21.4305 | 1800 | 0.8095          |
| 7.2292        | 22.0239 | 1850 | 0.7950          |
| 6.3362        | 22.6218 | 1900 | 0.7930          |
| 6.2422        | 23.2152 | 1950 | 0.8145          |
| 7.6344        | 23.8132 | 2000 | 0.7909          |
| 6.8542        | 24.4066 | 2050 | 0.7892          |
| 6.9861        | 25.0    | 2100 | 0.7946          |
| 6.5772        | 25.5979 | 2150 | 0.7902          |
| 6.5195        | 26.1913 | 2200 | 0.7990          |
| 6.7995        | 26.7892 | 2250 | 0.7958          |
| 6.1444        | 27.3827 | 2300 | 0.7956          |
| 6.8757        | 27.9806 | 2350 | 0.7945          |
| 6.9428        | 28.5740 | 2400 | 0.7901          |
| 7.4196        | 29.1674 | 2450 | 0.7935          |
| 6.5429        | 29.7653 | 2500 | 0.7935          |


### Framework versions

- PEFT 0.18.1
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2