Florence-2-FT-JP-OCR2

This model is a fine-tuned version of microsoft/Florence-2-base-ft on EtashGuha/JapaneseDocQA dataset. It achieves the following results on the evaluation set:

• Loss: 2.7551

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: 2
• eval_batch_size: 2
• seed: 42
• gradient_accumulation_steps: 4
• total_train_batch_size: 8
• 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: 7

Training results

Training Loss	Epoch	Step	Validation Loss
14.8441	0.5563	100	3.2737
14.1581	1.1168	200	3.1344
13.4486	1.6732	300	3.0362
13.287	2.2337	400	2.9634
12.9018	2.7900	500	2.9081
12.6016	3.3505	600	2.8683
12.5607	3.9068	700	2.8310
12.4259	4.4673	800	2.8060
12.2114	5.0278	900	2.7858
12.1777	5.5841	1000	2.7680
12.01	6.1446	1100	2.7604
12.0395	6.7010	1200	2.7551

Framework versions

• Transformers 4.48.0.dev0
• Pytorch 2.5.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0