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

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: 3.2269

## 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: 7e-06
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.4289        | 1.0   | 45   | 2.8658          |
| 1.7576        | 2.0   | 90   | 2.8422          |
| 1.4401        | 3.0   | 135  | 2.9391          |
| 1.2229        | 4.0   | 180  | 2.9810          |
| 1.0519        | 5.0   | 225  | 2.9622          |
| 0.9047        | 6.0   | 270  | 3.0516          |
| 0.8089        | 7.0   | 315  | 3.0336          |
| 0.7068        | 8.0   | 360  | 3.0954          |
| 0.6517        | 9.0   | 405  | 3.1408          |
| 0.5915        | 10.0  | 450  | 3.1432          |
| 0.5247        | 11.0  | 495  | 3.2247          |
| 0.5032        | 12.0  | 540  | 3.2057          |
| 0.4687        | 13.0  | 585  | 3.2391          |
| 0.4615        | 14.0  | 630  | 3.2328          |
| 0.4484        | 15.0  | 675  | 3.2269          |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.3.0
- Datasets 2.20.0
- Tokenizers 0.20.3