---
license: mit
tags:
- generated_from_trainer
model-index:
- name: testing_img_token
  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. -->

# testing_img_token

This model is a fine-tuned version of [SCUT-DLVCLab/lilt-roberta-en-base](https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9187
- Eading: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2}
- Ext: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9}
- Ub heading: {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15}
- Overall Precision: 0.0
- Overall Recall: 0.0
- Overall F1: 0.0
- Overall Accuracy: 0.4848

## 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: 0.0005
- 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
- training_steps: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Eading                                                    | Ext                                                       | Ub heading                                                 | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------------------------------------------------------:|:---------------------------------------------------------:|:----------------------------------------------------------:|:-----------------:|:--------------:|:----------:|:----------------:|
| 1.4635        | 1.43  | 10   | 1.2178          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0               | 0.0            | 0.0        | 0.4848           |
| 1.2206        | 2.86  | 20   | 1.0016          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0               | 0.0            | 0.0        | 0.4848           |
| 1.0569        | 4.29  | 30   | 0.9783          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0               | 0.0            | 0.0        | 0.4848           |
| 1.0201        | 5.71  | 40   | 0.9273          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0               | 0.0            | 0.0        | 0.4848           |
| 0.9888        | 7.14  | 50   | 0.9187          | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 2} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 9} | {'precision': 0.0, 'recall': 0.0, 'f1': 0.0, 'number': 15} | 0.0               | 0.0            | 0.0        | 0.4848           |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2