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# checkpoints

This model is a fine-tuned version of [kavg/LiLT-RE-EN](https://huggingface.co/kavg/LiLT-RE-EN) on the xfun dataset.
It achieves the following results on the evaluation set:
- Precision: 0.4858
- Recall: 0.6821
- F1: 0.5675
- Loss: 0.1078

## 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-05
- train_batch_size: 8
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 4000

### Training results

| Training Loss | Epoch  | Step | F1     | Validation Loss | Precision | Recall |
|:-------------:|:------:|:----:|:------:|:---------------:|:---------:|:------:|
| 0.0774        | 83.33  | 500  | 0.5337 | 0.1350          | 0.4634    | 0.6291 |
| 0.0331        | 166.67 | 1000 | 0.5675 | 0.1078          | 0.4858    | 0.6821 |
| 0.0246        | 250.0  | 1500 | 0.5810 | 0.1576          | 0.5024    | 0.6887 |
| 0.0204        | 333.33 | 2000 | 0.5714 | 0.1995          | 0.5025    | 0.6623 |
| 0.0098        | 416.67 | 2500 | 0.5665 | 0.2133          | 0.5026    | 0.6490 |
| 0.0078        | 500.0  | 3000 | 0.5739 | 0.2444          | 0.5103    | 0.6556 |
| 0.0075        | 583.33 | 3500 | 0.5681 | 0.2340          | 0.5052    | 0.6490 |
| 0.015         | 666.67 | 4000 | 0.5076 | 0.6623          | 0.5747    | 0.2503 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["xfun"], "metrics": ["precision", "recall", "f1"], "base_model": "kavg/LiLT-RE-EN", "model-index": [{"name": "checkpoints", "results": []}]}
transformers safetensors lilt generated_from_trainer dataset:xfun base_model:kavg/LiLT-RE-EN license:mit endpoints_compatible region:us