SmolVLM-256M-ScreenTask

This model is a fine-tuned version of HuggingFaceTB/SmolVLM-256M-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.8402

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 OptimizerNames.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: 0.35
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
2.857	0.0599	20	2.7762
1.8633	0.1199	40	1.8233
1.1164	0.1798	60	1.0640
0.8947	0.2397	80	0.8909
0.8471	0.2996	100	0.8402

Framework versions

• PEFT 0.18.0
• Transformers 4.57.3
• Pytorch 2.9.0+cu126
• Datasets 4.0.0
• Tokenizers 0.22.1