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metadata
library_name: transformers
license: mit
base_model: microsoft/Florence-2-base-ft
tags:
  - generated_from_trainer
model-index:
  - name: Florence-2-FT-JP-OCR2
    results: []
datasets:
  - EtashGuha/JapaneseDocQA
language:
  - ja

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