Vision Language Model
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VL
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Teera/Llama-3.2v-COT-Thai is a fine-tuned model based on Llama-3.2V-11B-co, developed with inspiration from the LLaVA-CoT framework.
The concept was introduced in LLaVA-CoT: Let Vision Language Models Reason Step-by-Step.
The model is trained on the LLaVA-CoT-100k dataset, which has been preprocessed and translated into the Thai language.
The model is finetuned on llama-recipes with the following settings. Using the same setting should accurately reproduce our results.
Parameter | Value |
---|---|
FSDP | enabled |
lr | 1e-4 |
num_epochs | 1 |
batch_size_training | 2 |
use_fast_kernels | True |
run_validation | False |
batching_strategy | padding |
context_length | 4096 |
gradient_accumulation_steps | 1 |
gradient_clipping | False |
gradient_clipping_threshold | 1.0 |
weight_decay | 0.0 |
gamma | 0.85 |
seed | 42 |
use_fp16 | False |
mixed_precision | True |
The model may generate biased or offensive content, similar to other VLMs, due to limitations in the training data. Technically, the model's performance in aspects like instruction following still falls short of leading industry models.
Base model
meta-llama/Llama-3.2-11B-Vision-Instruct