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--- |
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library_name: peft |
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license: apache-2.0 |
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base_model: HuggingFaceTB/SmolVLM-256M-Instruct |
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tags: |
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- base_model:adapter:HuggingFaceTB/SmolVLM-256M-Instruct |
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- lora |
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- transformers |
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- image |
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- gui |
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model-index: |
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- name: SmolVLM-256M-ScreenTask |
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results: [] |
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datasets: |
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- macpaw-research/Screen2AX-Task |
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language: |
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- en |
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pipeline_tag: image-text-to-text |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# SmolVLM-256M-ScreenTask |
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This model is a fine-tuned version of [HuggingFaceTB/SmolVLM-256M-Instruct](https://huggingface.co/HuggingFaceTB/SmolVLM-256M-Instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8402 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 0.35 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.857 | 0.0599 | 20 | 2.7762 | |
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| 1.8633 | 0.1199 | 40 | 1.8233 | |
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| 1.1164 | 0.1798 | 60 | 1.0640 | |
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| 0.8947 | 0.2397 | 80 | 0.8909 | |
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| 0.8471 | 0.2996 | 100 | 0.8402 | |
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### Framework versions |
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- PEFT 0.18.0 |
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- Transformers 4.57.3 |
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- Pytorch 2.9.0+cu126 |
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- Datasets 4.0.0 |
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- Tokenizers 0.22.1 |
