FT-SmolVLM-256M-Instruct
This model is a fine-tuned version of HuggingFaceTB/SmolVLM-256M-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: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- 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: 5
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0
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Model tree for revitotan/FT-SmolVLM-256M-Instruct-Helmet
Base model
HuggingFaceTB/SmolLM2-135M
Quantized
HuggingFaceTB/SmolLM2-135M-Instruct
Quantized
HuggingFaceTB/SmolVLM-256M-Instruct