--- base_model: openbmb/MiniCPM-V-2_6 library_name: peft tags: - generated_from_trainer model-index: - name: MiniCPM-V-2_6_lora_20240916_155621 results: [] --- # MiniCPM-V-2_6_lora_20240916_155621 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: 0.2347 ## 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 | |:-------------:|:------:|:----:|:---------------:| | 0.1221 | 0.2430 | 100 | 0.2809 | | 0.1534 | 0.4860 | 200 | 0.2695 | | 0.1055 | 0.7290 | 300 | 0.2456 | | 0.0828 | 0.9721 | 400 | 0.2336 | | 0.1028 | 1.2151 | 500 | 0.2355 | | 0.0444 | 1.4581 | 600 | 0.2294 | | 0.054 | 1.7011 | 700 | 0.2347 | ### Framework versions - PEFT 0.12.0 - Transformers 4.40.0 - Pytorch 2.1.2+cu121 - Tokenizers 0.19.1