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---
base_model: openbmb/MiniCPM-V-2_6
library_name: peft
tags:
- generated_from_trainer
model-index:
- name: miniCPM_finetune_lora_viet_vqa
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. -->
# miniCPM_finetune_lora_viet_vqa
This model is a fine-tuned version of [openbmb/MiniCPM-V-2_6](https://huggingface.co/openbmb/MiniCPM-V-2_6) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6850
## 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: 1e-06
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 5.0
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.1566 | 1.3889 | 100 | 2.0881 |
| 1.8447 | 2.7778 | 200 | 1.8452 |
| 1.7103 | 4.1667 | 300 | 1.6850 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.40.0
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1 |