---
library_name: transformers
license: other
base_model: openbmb/MiniCPM-V-4.6
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: minicpmv46_sheetmusic_full
  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. -->

# minicpmv46_sheetmusic_full

This model is a fine-tuned version of [openbmb/MiniCPM-V-4.6](https://huggingface.co/openbmb/MiniCPM-V-4.6) on the sheetmusic_train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0018

## 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-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- total_eval_batch_size: 4
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.05
- num_epochs: 4.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.4366        | 0.1664 | 100  | 0.4435          |
| 0.0412        | 0.3327 | 200  | 0.0465          |
| 0.0205        | 0.4991 | 300  | 0.0163          |
| 0.0080        | 0.6655 | 400  | 0.0084          |
| 0.0080        | 0.8319 | 500  | 0.0065          |
| 0.0072        | 0.9982 | 600  | 0.0072          |
| 0.0094        | 1.1630 | 700  | 0.0046          |
| 0.0038        | 1.3294 | 800  | 0.0048          |
| 0.0070        | 1.4958 | 900  | 0.0042          |
| 0.0013        | 1.6622 | 1000 | 0.0032          |
| 0.0020        | 1.8285 | 1100 | 0.0032          |
| 0.0011        | 1.9949 | 1200 | 0.0028          |
| 0.0030        | 2.1597 | 1300 | 0.0023          |
| 0.0018        | 2.3261 | 1400 | 0.0024          |
| 0.0007        | 2.4925 | 1500 | 0.0022          |
| 0.0048        | 2.6588 | 1600 | 0.0021          |
| 0.0017        | 2.8252 | 1700 | 0.0020          |
| 0.0019        | 2.9916 | 1800 | 0.0019          |
| 0.0006        | 3.1564 | 1900 | 0.0019          |
| 0.0004        | 3.3228 | 2000 | 0.0018          |
| 0.0007        | 3.4891 | 2100 | 0.0018          |
| 0.0004        | 3.6555 | 2200 | 0.0018          |
| 0.0009        | 3.8219 | 2300 | 0.0018          |
| 0.0005        | 3.9882 | 2400 | 0.0018          |
| 0.0001        | 4.0    | 2408 | 0.0018          |


### Framework versions

- Transformers 5.7.0
- Pytorch 2.8.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2