File size: 2,051 Bytes
a89e3d0 a182bf6 a89e3d0 9dbdfd1 a89e3d0 a182bf6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 |
---
library_name: transformers
license: mit
base_model: microsoft/Florence-2-base-ft
tags:
- generated_from_trainer
model-index:
- name: Florence-2-FT-JP-OCR
results: []
datasets:
- EtashGuha/JapaneseDocQA
---
<!-- 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-OCR
This model is a fine-tuned version of [microsoft/Florence-2-base-ft](https://huggingface.co/microsoft/Florence-2-base-ft) on [EtashGuha/JapaneseDocQA](https://huggingface.co/datasets/EtashGuha/JapaneseDocQA) dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5827
## 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: 5e-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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 14.3012 | 0.9662 | 100 | 3.1360 |
| 12.8837 | 1.9275 | 200 | 2.9369 |
| 12.1693 | 2.8889 | 300 | 2.7978 |
| 11.6903 | 3.8502 | 400 | 2.7166 |
| 11.3443 | 4.8116 | 500 | 2.6688 |
| 11.1585 | 5.7729 | 600 | 2.6340 |
| 10.9682 | 6.7343 | 700 | 2.6140 |
| 10.9556 | 7.6957 | 800 | 2.5960 |
| 10.7355 | 8.6570 | 900 | 2.5882 |
| 10.6794 | 9.6184 | 1000 | 2.5827 |
### Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0 |