|
|
--- |
|
|
library_name: peft |
|
|
license: apache-2.0 |
|
|
base_model: lightonai/LightOnOCR-1B-1025 |
|
|
tags: |
|
|
- base_model:adapter:lightonai/LightOnOCR-1B-1025 |
|
|
- lora |
|
|
- transformers |
|
|
pipeline_tag: text-generation |
|
|
model-index: |
|
|
- name: lightonocr-ft-iam |
|
|
results: [] |
|
|
datasets: |
|
|
- HuggingFaceM4/FineVision |
|
|
--- |
|
|
|
|
|
<!-- 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. --> |
|
|
|
|
|
# lightonocr-ft-iam |
|
|
|
|
|
This model is a fine-tuned version of [lightonai/LightOnOCR-1B-1025](https://huggingface.co/lightonai/LightOnOCR-1B-1025) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.4395 |
|
|
|
|
|
## 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: 6e-05 |
|
|
- train_batch_size: 4 |
|
|
- eval_batch_size: 6 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 4 |
|
|
- total_train_batch_size: 16 |
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- lr_scheduler_warmup_steps: 10 |
|
|
- training_steps: 100 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:------:|:----:|:---------------:| |
|
|
| 3.1522 | 0.1661 | 50 | 0.4954 | |
|
|
| 1.6662 | 0.3322 | 100 | 0.4395 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- PEFT 0.18.0 |
|
|
- Transformers 5.0.0.dev0 |
|
|
- Pytorch 2.9.1 |
|
|
- Datasets 4.4.1 |
|
|
- Tokenizers 0.22.1 |
