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blip2-vqa-pathology
duythanh1022/blip2-vqa-pathology
blip2-vqa-pathology is a machine learning model from duythanh1022. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- Access
- Public
- Created
- May 26, 2025
- Updated
- May 27, 2025
- SHA
- 359bcd5b
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
blip2-vqa-pathology
This model is a fine-tuned version of ybelkada/blip2-opt-2.7b-fp16-sharded on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0001
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.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.0002 | 0.5814 | 500 | 0.0001 |
| 0.0001 | 1.1628 | 1000 | 0.0001 |
| 0.0001 | 1.7442 | 1500 | 0.0001 |
Framework versions
- PEFT 0.15.2.dev0
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
- Library
- peft
- Created
- May 26, 2025
- Updated
- May 27, 2025