---
library_name: transformers
license: mit
base_model: microsoft/Florence-2-base-ft
tags:
- generated_from_trainer
model-index:
- name: Florence-2-FT-JP-OCR3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# Florence-2-FT-JP-OCR3

This model is a fine-tuned version of [microsoft/Florence-2-base-ft](https://huggingface.co/microsoft/Florence-2-base-ft) on an unknown 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