| --- |
| library_name: transformers |
| license: mit |
| base_model: Salesforce/blip2-opt-2.7b |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: blip-gqa-ft2 |
| results: [] |
| --- |
| |
| <!-- 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. --> |
|
|
| # blip-gqa-ft2 |
|
|
| This model is a fine-tuned version of [Salesforce/blip2-opt-2.7b](https://huggingface.co/Salesforce/blip2-opt-2.7b) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 4.3643 |
|
|
| ## 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: 12 |
| - eval_batch_size: 12 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 48 |
| - 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: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 2.3951 | 1.0 | 834 | 2.3899 | |
| | 2.1612 | 2.0 | 1668 | 2.3136 | |
| | 1.9679 | 3.0 | 2502 | 2.3081 | |
| | 1.6637 | 4.0 | 3336 | 2.4092 | |
| | 1.3671 | 5.0 | 4170 | 2.5614 | |
| | 1.0208 | 6.0 | 5004 | 2.8319 | |
| | 0.7236 | 7.0 | 5838 | 3.1588 | |
| | 0.4731 | 8.0 | 6672 | 3.5582 | |
| | 0.3325 | 9.0 | 7506 | 3.9899 | |
| | 0.2296 | 9.9886 | 8330 | 4.3643 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.51.3 |
| - Pytorch 2.5.1+cu121 |
| - Datasets 3.5.0 |
| - Tokenizers 0.21.1 |
| |
