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SmolVLM-Instruct-vqav2
This model is a fine-tuned version of HuggingFaceTB/SmolVLM-Instruct on an unknown 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use paged_adamw_8bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 1
Framework versions
- PEFT 0.14.0
- Transformers 4.46.2
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.20.3
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Model tree for ivelin/SmolVLM-Instruct-vqav2
Base model
HuggingFaceTB/SmolLM2-1.7B
Quantized
HuggingFaceTB/SmolLM2-1.7B-Instruct
Quantized
HuggingFaceTB/SmolVLM-Instruct