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---
base_model: openbmb/MiniCPM-V-2_6
library_name: peft
tags:
- generated_from_trainer
model-index:
- name: MiniCPM-V-2_6_lora_20240917_011727
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_20240917_011727
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: 1.3224
## 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: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 8
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.3412 | 0.0349 | 100 | 1.3380 |
| 1.3477 | 0.0698 | 200 | 1.3300 |
| 1.3057 | 0.1047 | 300 | 1.3255 |
| 1.3116 | 0.1396 | 400 | 1.3224 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.40.0
- Pytorch 2.1.2+cu121
- Tokenizers 0.19.1 |