blip2-finetuned-ai2d
This model is a fine-tuned version of Salesforce/blip-vqa-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3500
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 8
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.3867 | 1.4380 | 50 | 0.3808 |
| 0.3498 | 2.8759 | 100 | 0.3536 |
| 0.3525 | 4.2920 | 150 | 0.3529 |
| 0.3497 | 5.7299 | 200 | 0.3553 |
| 0.321 | 7.1460 | 250 | 0.3500 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for Ashkchamp/blip2-finetuned-ai2d
Base model
Salesforce/blip-vqa-base