| --- |
| license: apache-2.0 |
| base_model: HuggingFaceM4/idefics2-8b |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: idefics2-8b-path_vqa-finetuned-tutorial |
| 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. --> |
|
|
| # idefics2-8b-path_vqa-finetuned-tutorial |
| |
| This model is a fine-tuned version of [HuggingFaceM4/idefics2-8b](https://huggingface.co/HuggingFaceM4/idefics2-8b) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 1.0688 |
| |
| ## 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: 2 |
| - eval_batch_size: 2 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 16 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_steps: 50 |
| - num_epochs: 2 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:----:|:---------------:| |
| | 6.0779 | 0.16 | 10 | 3.3574 | |
| | 2.0221 | 0.32 | 20 | 1.2580 | |
| | 1.0361 | 0.48 | 30 | 1.0355 | |
| | 0.7289 | 0.64 | 40 | 1.0705 | |
| | 0.6758 | 0.8 | 50 | 1.0496 | |
| | 0.5689 | 0.96 | 60 | 1.0893 | |
| | 0.4038 | 1.12 | 70 | 1.1230 | |
| | 0.3773 | 1.28 | 80 | 1.0498 | |
| | 0.3227 | 1.44 | 90 | 1.1104 | |
| | 0.2934 | 1.6 | 100 | 1.0788 | |
| | 0.2968 | 1.76 | 110 | 1.0667 | |
| | 0.3099 | 1.92 | 120 | 1.0688 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.0.dev0 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.19.2 |
| - Tokenizers 0.19.1 |
| |
