Florence-2-base-TableDetection
This model is a fine-tuned version of microsoft/Florence-2-base-ft on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.0755
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: 2e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Use 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 |
|---|---|---|---|
| 10.4264 | 1.0 | 805 | 2.1765 |
| 8.8927 | 1.9978 | 1608 | 2.0755 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for aipib/Florence-2-base-TableDetection
Base model
microsoft/Florence-2-base-ft