---
license: mit
base_model: microsoft/Florence-2-large-ft
tags:
- image-text-to-text
- generated_from_trainer
model-index:
- name: Florence-2-large-TableDetection
  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-large-TableDetection

This model is a fine-tuned version of [microsoft/Florence-2-large-ft](https://huggingface.co/microsoft/Florence-2-large-ft) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7601

## 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: 1e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.3199        | 1.0   | 169  | 1.0372          |
| 0.7922        | 2.0   | 338  | 0.9169          |
| 0.6824        | 3.0   | 507  | 0.8411          |
| 0.6109        | 4.0   | 676  | 0.8168          |
| 0.5752        | 5.0   | 845  | 0.7915          |
| 0.5605        | 6.0   | 1014 | 0.7862          |
| 0.5291        | 7.0   | 1183 | 0.7740          |
| 0.517         | 8.0   | 1352 | 0.7683          |
| 0.5139        | 9.0   | 1521 | 0.7642          |
| 0.5005        | 10.0  | 1690 | 0.7601          |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1