---
base_model: openbmb/MiniCPM-V-2_6
library_name: peft
tags:
- generated_from_trainer
model-index:
- name: MiniCPM-V-2_6_lora_20240915_181155
  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-V-2_6_lora_20240915_181155

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: 0.1966

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.1465        | 0.7055 | 100  | 0.1790          |
| 0.0339        | 1.4109 | 200  | 0.1891          |
| 0.033         | 2.1164 | 300  | 0.1994          |
| 0.0333        | 2.8219 | 400  | 0.1966          |


### Framework versions

- PEFT 0.12.0
- Transformers 4.40.0
- Pytorch 2.1.2+cu121
- Tokenizers 0.19.1