florence2-pitvqa-finetuned
This model is a fine-tuned version of microsoft/Florence-2-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7384
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: 4
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 20
- training_steps: 200
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.1616 | 6.25 | 50 | 3.7871 |
| 1.696 | 12.5 | 100 | 1.3849 |
| 1.0616 | 18.75 | 150 | 0.8380 |
| 0.9614 | 25.0 | 200 | 0.7384 |
Framework versions
- PEFT 0.18.1
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.2
- Tokenizers 0.22.2