---
license: apache-2.0
base_model: ICT2214Team7/RoBERTa_Test_Training
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: RoBERTa_Combined_Generated_v2_2000_Fold4
  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. -->

# RoBERTa_Combined_Generated_v2_2000_Fold4

This model is a fine-tuned version of [ICT2214Team7/RoBERTa_Test_Training](https://huggingface.co/ICT2214Team7/RoBERTa_Test_Training) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0526
- Precision: 0.8689
- Recall: 0.9276
- F1: 0.8973
- Accuracy: 0.9856
- Report: {'AGE': {'precision': 0.9469026548672567, 'recall': 1.0, 'f1-score': 0.9727272727272728, 'support': 107}, 'LOC': {'precision': 0.7831325301204819, 'recall': 0.9090909090909091, 'f1-score': 0.8414239482200647, 'support': 286}, 'NAT': {'precision': 0.9096774193548387, 'recall': 0.9657534246575342, 'f1-score': 0.93687707641196, 'support': 146}, 'ORG': {'precision': 0.8943661971830986, 'recall': 0.8639455782312925, 'f1-score': 0.8788927335640138, 'support': 147}, 'PER': {'precision': 0.930379746835443, 'recall': 0.9363057324840764, 'f1-score': 0.9333333333333332, 'support': 157}, 'micro avg': {'precision': 0.8688888888888889, 'recall': 0.9276393831553974, 'f1-score': 0.8973034997131383, 'support': 843}, 'macro avg': {'precision': 0.8928917096722238, 'recall': 0.9350191288927625, 'f1-score': 0.912650872851329, 'support': 843}, 'weighted avg': {'precision': 0.872655803262326, 'recall': 0.9276393831553974, 'f1-score': 0.8982724622730086, 'support': 843}}

## 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-05
- 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
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Report                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
| No log        | 1.0   | 160  | 0.0509          | 0.8521    | 0.9229 | 0.8861 | 0.9840   | {'AGE': {'precision': 0.963963963963964, 'recall': 1.0, 'f1-score': 0.9816513761467891, 'support': 107}, 'LOC': {'precision': 0.7602339181286549, 'recall': 0.9090909090909091, 'f1-score': 0.8280254777070064, 'support': 286}, 'NAT': {'precision': 0.875, 'recall': 0.958904109589041, 'f1-score': 0.9150326797385621, 'support': 146}, 'ORG': {'precision': 0.8936170212765957, 'recall': 0.8571428571428571, 'f1-score': 0.875, 'support': 147}, 'PER': {'precision': 0.9119496855345912, 'recall': 0.9235668789808917, 'f1-score': 0.9177215189873418, 'support': 157}, 'micro avg': {'precision': 0.8521358159912377, 'recall': 0.9228944246737841, 'f1-score': 0.8861047835990888, 'support': 843}, 'macro avg': {'precision': 0.8809529177807611, 'recall': 0.9297409509607398, 'f1-score': 0.9034862105159398, 'support': 843}, 'weighted avg': {'precision': 0.8574838048464174, 'recall': 0.9228944246737841, 'f1-score': 0.8874899568146536, 'support': 843}}                        |
| No log        | 2.0   | 320  | 0.0581          | 0.8673    | 0.9383 | 0.9014 | 0.9842   | {'AGE': {'precision': 0.9469026548672567, 'recall': 1.0, 'f1-score': 0.9727272727272728, 'support': 107}, 'LOC': {'precision': 0.7922848664688428, 'recall': 0.9335664335664335, 'f1-score': 0.8571428571428572, 'support': 286}, 'NAT': {'precision': 0.9038461538461539, 'recall': 0.9657534246575342, 'f1-score': 0.9337748344370861, 'support': 146}, 'ORG': {'precision': 0.8698630136986302, 'recall': 0.8639455782312925, 'f1-score': 0.8668941979522184, 'support': 147}, 'PER': {'precision': 0.93125, 'recall': 0.9490445859872612, 'f1-score': 0.9400630914826499, 'support': 157}, 'micro avg': {'precision': 0.8673245614035088, 'recall': 0.9383155397390273, 'f1-score': 0.9014245014245014, 'support': 843}, 'macro avg': {'precision': 0.8888293377761768, 'recall': 0.9424620044885043, 'f1-score': 0.9141204507484169, 'support': 843}, 'weighted avg': {'precision': 0.8706402222492559, 'recall': 0.9383155397390273, 'f1-score': 0.9022291264700381, 'support': 843}}       |
| No log        | 3.0   | 480  | 0.0526          | 0.8689    | 0.9276 | 0.8973 | 0.9856   | {'AGE': {'precision': 0.9469026548672567, 'recall': 1.0, 'f1-score': 0.9727272727272728, 'support': 107}, 'LOC': {'precision': 0.7831325301204819, 'recall': 0.9090909090909091, 'f1-score': 0.8414239482200647, 'support': 286}, 'NAT': {'precision': 0.9096774193548387, 'recall': 0.9657534246575342, 'f1-score': 0.93687707641196, 'support': 146}, 'ORG': {'precision': 0.8943661971830986, 'recall': 0.8639455782312925, 'f1-score': 0.8788927335640138, 'support': 147}, 'PER': {'precision': 0.930379746835443, 'recall': 0.9363057324840764, 'f1-score': 0.9333333333333332, 'support': 157}, 'micro avg': {'precision': 0.8688888888888889, 'recall': 0.9276393831553974, 'f1-score': 0.8973034997131383, 'support': 843}, 'macro avg': {'precision': 0.8928917096722238, 'recall': 0.9350191288927625, 'f1-score': 0.912650872851329, 'support': 843}, 'weighted avg': {'precision': 0.872655803262326, 'recall': 0.9276393831553974, 'f1-score': 0.8982724622730086, 'support': 843}} |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1