sft_aitw_all
This model is a fine-tuned version of Qwen/Qwen2-VL-2B-Instruct on the vl_sft_data_aitw dataset.
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: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0
Training results
Framework versions
- PEFT 0.12.0
- Transformers 4.45.0
- Pytorch 2.4.1+cu121
- Datasets 2.20.0
- Tokenizers 0.20.1
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Model tree for cjfcsjt/142_sft_aitw_all_2b
Base model
Qwen/Qwen2-VL-2B-Instruct