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---
library_name: peft
license: apache-2.0
base_model: AdaptLLM/biomed-Qwen2-VL-2B-Instruct
tags:
- llama-factory
- generated_from_trainer
model-index:
- name: qwenvl-2B-cadica-direction-scale4
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. -->
# qwenvl-2B-cadica-direction-scale4
This model is a fine-tuned version of [AdaptLLM/biomed-Qwen2-VL-2B-Instruct](https://huggingface.co/AdaptLLM/biomed-Qwen2-VL-2B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0022
- Num Input Tokens Seen: 11980800
## 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: 0.0001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 6
- total_train_batch_size: 24
- total_eval_batch_size: 4
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 1200
### Training results
| Training Loss | Epoch | Step | Validation Loss | Input Tokens Seen |
|:-------------:|:------:|:----:|:---------------:|:-----------------:|
| 0.3441 | 0.0258 | 50 | 0.3383 | 499200 |
| 0.2274 | 0.0515 | 100 | 0.1866 | 998400 |
| 0.0667 | 0.0773 | 150 | 0.0967 | 1497600 |
| 0.0459 | 0.1030 | 200 | 0.0996 | 1996800 |
| 0.0805 | 0.1288 | 250 | 0.0559 | 2496000 |
| 0.0381 | 0.1545 | 300 | 0.0309 | 2995200 |
| 0.1761 | 0.1803 | 350 | 0.0439 | 3494400 |
| 0.0146 | 0.2060 | 400 | 0.0244 | 3993600 |
| 0.0157 | 0.2318 | 450 | 0.0067 | 4492800 |
| 0.0122 | 0.2575 | 500 | 0.0080 | 4992000 |
| 0.0339 | 0.2833 | 550 | 0.0034 | 5491200 |
| 0.0217 | 0.3090 | 600 | 0.0133 | 5990400 |
| 0.0327 | 0.3348 | 650 | 0.0210 | 6489600 |
| 0.0267 | 0.3605 | 700 | 0.0053 | 6988800 |
| 0.014 | 0.3863 | 750 | 0.0053 | 7488000 |
| 0.0065 | 0.4121 | 800 | 0.0068 | 7987200 |
| 0.0306 | 0.4378 | 850 | 0.0072 | 8486400 |
| 0.0063 | 0.4636 | 900 | 0.0107 | 8985600 |
| 0.0415 | 0.4893 | 950 | 0.0072 | 9484800 |
| 0.0547 | 0.5151 | 1000 | 0.0007 | 9984000 |
| 0.0007 | 0.5408 | 1050 | 0.0568 | 10483200 |
| 0.0056 | 0.5666 | 1100 | 0.0004 | 10982400 |
| 0.0127 | 0.5923 | 1150 | 0.0000 | 11481600 |
| 0.0038 | 0.6181 | 1200 | 0.0022 | 11980800 |
### Framework versions
- PEFT 0.12.0
- Transformers 4.47.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3 |