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# checkpoints

This model is a fine-tuned version of [nielsr/lilt-xlm-roberta-base](https://huggingface.co/nielsr/lilt-xlm-roberta-base) on the xfun dataset.
It achieves the following results on the evaluation set:
- Precision: 0.4301
- Recall: 0.7110
- F1: 0.5360
- Loss: 0.1529

## 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: 10000

### Training results

| Training Loss | Epoch  | Step  | F1     | Validation Loss | Precision | Recall |
|:-------------:|:------:|:-----:|:------:|:---------------:|:---------:|:------:|
| 0.1937        | 14.71  | 500   | 0      | 0.3651          | 0         | 0      |
| 0.1605        | 29.41  | 1000  | 0.2033 | 0.3287          | 0.4497    | 0.1314 |
| 0.1037        | 44.12  | 1500  | 0.4002 | 0.3697          | 0.4064    | 0.3941 |
| 0.0952        | 58.82  | 2000  | 0.4622 | 0.4930          | 0.3722    | 0.6097 |
| 0.0503        | 73.53  | 2500  | 0.4886 | 0.6168          | 0.3840    | 0.6716 |
| 0.0657        | 88.24  | 3000  | 0.4949 | 0.3243          | 0.3857    | 0.6901 |
| 0.0262        | 102.94 | 3500  | 0.5050 | 0.2840          | 0.4005    | 0.6832 |
| 0.0238        | 117.65 | 4000  | 0.5205 | 0.4294          | 0.4156    | 0.6963 |
| 0.0258        | 132.35 | 4500  | 0.5198 | 0.0871          | 0.4183    | 0.6862 |
| 0.0136        | 147.06 | 5000  | 0.5216 | 0.1642          | 0.4143    | 0.7040 |
| 0.0259        | 161.76 | 5500  | 0.5270 | 0.3042          | 0.4223    | 0.7009 |
| 0.0107        | 176.47 | 6000  | 0.5261 | 0.2665          | 0.4208    | 0.7017 |
| 0.0074        | 191.18 | 6500  | 0.5345 | 0.2884          | 0.4258    | 0.7179 |
| 0.0105        | 205.88 | 7000  | 0.5429 | 0.2051          | 0.4414    | 0.7048 |
| 0.0079        | 220.59 | 7500  | 0.4348 | 0.7063          | 0.5383    | 0.3553 |
| 0.0075        | 235.29 | 8000  | 0.4301 | 0.7110          | 0.5360    | 0.1529 |
| 0.0026        | 250.0  | 8500  | 0.4263 | 0.7264          | 0.5373    | 0.4010 |
| 0.001         | 264.71 | 9000  | 0.4352 | 0.7133          | 0.5406    | 0.2411 |
| 0.003         | 279.41 | 9500  | 0.4298 | 0.7141          | 0.5366    | 0.2696 |
| 0.0118        | 294.12 | 10000 | 0.4284 | 0.7172          | 0.5364    | 0.2205 |


### 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": "nielsr/lilt-xlm-roberta-base", "model-index": [{"name": "checkpoints", "results": []}]}
transformers safetensors lilt generated_from_trainer dataset:xfun base_model:nielsr/lilt-xlm-roberta-base license:mit endpoints_compatible region:us