florence2_output
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: 1.5346
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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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: 50
- training_steps: 500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.7452 | 25.0 | 100 | 1.7258 |
| 1.1957 | 50.0 | 200 | 1.4125 |
| 1.1343 | 75.0 | 300 | 1.4571 |
| 1.0557 | 100.0 | 400 | 1.5572 |
| 1.0336 | 125.0 | 500 | 1.5346 |
Framework versions
- PEFT 0.18.1
- Transformers 4.57.3
- Pytorch 2.9.1+cu128
- Datasets 4.4.2
- Tokenizers 0.22.2
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Model tree for mmrech/florence2_output
Base model
microsoft/Florence-2-base