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---
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_Fold3
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_Fold3
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: 0.0492
- Precision: 0.8777
- Recall: 0.9317
- F1: 0.9039
- Accuracy: 0.9864
- Report: {'AGE': {'precision': 0.956140350877193, 'recall': 0.990909090909091, 'f1-score': 0.9732142857142858, 'support': 110}, 'LOC': {'precision': 0.7917888563049853, 'recall': 0.9342560553633218, 'f1-score': 0.8571428571428571, 'support': 289}, 'NAT': {'precision': 0.9137931034482759, 'recall': 0.9464285714285714, 'f1-score': 0.9298245614035087, 'support': 168}, 'ORG': {'precision': 0.9090909090909091, 'recall': 0.8783783783783784, 'f1-score': 0.8934707903780069, 'support': 148}, 'PER': {'precision': 0.9375, 'recall': 0.9202453987730062, 'f1-score': 0.9287925696594428, 'support': 163}, 'micro avg': {'precision': 0.8776824034334764, 'recall': 0.9316628701594533, 'f1-score': 0.903867403314917, 'support': 878}, 'macro avg': {'precision': 0.9016626439442726, 'recall': 0.9340434989704736, 'f1-score': 0.9164890128596201, 'support': 878}, 'weighted avg': {'precision': 0.8825485352999964, 'recall': 0.9316628701594533, 'f1-score': 0.9050173682107981, 'support': 878}}
## 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 | 0.0674 | 0.8385 | 0.9226 | 0.8785 | 0.9800 | {'AGE': {'precision': 0.9478260869565217, 'recall': 0.990909090909091, 'f1-score': 0.9688888888888889, 'support': 110}, 'LOC': {'precision': 0.7355371900826446, 'recall': 0.9238754325259516, 'f1-score': 0.8190184049079754, 'support': 289}, 'NAT': {'precision': 0.8722222222222222, 'recall': 0.9345238095238095, 'f1-score': 0.9022988505747127, 'support': 168}, 'ORG': {'precision': 0.8680555555555556, 'recall': 0.8445945945945946, 'f1-score': 0.8561643835616439, 'support': 148}, 'PER': {'precision': 0.926829268292683, 'recall': 0.9325153374233128, 'f1-score': 0.9296636085626913, 'support': 163}, 'micro avg': {'precision': 0.8385093167701864, 'recall': 0.9225512528473804, 'f1-score': 0.878524945770065, 'support': 878}, 'macro avg': {'precision': 0.8700940646219253, 'recall': 0.925283652995352, 'f1-score': 0.8952068272991823, 'support': 878}, 'weighted avg': {'precision': 0.8461387742441511, 'recall': 0.9225512528473804, 'f1-score': 0.8805328025689936, 'support': 878}} |
| No log | 2.0 | 320 | 0.0455 | 0.8674 | 0.9237 | 0.8946 | 0.9857 | {'AGE': {'precision': 0.9557522123893806, 'recall': 0.9818181818181818, 'f1-score': 0.968609865470852, 'support': 110}, 'LOC': {'precision': 0.7800586510263929, 'recall': 0.9204152249134948, 'f1-score': 0.8444444444444444, 'support': 289}, 'NAT': {'precision': 0.8920454545454546, 'recall': 0.9345238095238095, 'f1-score': 0.9127906976744186, 'support': 168}, 'ORG': {'precision': 0.896551724137931, 'recall': 0.8783783783783784, 'f1-score': 0.8873720136518771, 'support': 148}, 'PER': {'precision': 0.9375, 'recall': 0.9202453987730062, 'f1-score': 0.9287925696594428, 'support': 163}, 'micro avg': {'precision': 0.8673796791443851, 'recall': 0.9236902050113895, 'f1-score': 0.894649751792609, 'support': 878}, 'macro avg': {'precision': 0.8923816084198318, 'recall': 0.9270761986813743, 'f1-score': 0.908401918180207, 'support': 878}, 'weighted avg': {'precision': 0.8723638781839517, 'recall': 0.9236902050113895, 'f1-score': 0.8959733641577534, 'support': 878}} |
| No log | 3.0 | 480 | 0.0492 | 0.8777 | 0.9317 | 0.9039 | 0.9864 | {'AGE': {'precision': 0.956140350877193, 'recall': 0.990909090909091, 'f1-score': 0.9732142857142858, 'support': 110}, 'LOC': {'precision': 0.7917888563049853, 'recall': 0.9342560553633218, 'f1-score': 0.8571428571428571, 'support': 289}, 'NAT': {'precision': 0.9137931034482759, 'recall': 0.9464285714285714, 'f1-score': 0.9298245614035087, 'support': 168}, 'ORG': {'precision': 0.9090909090909091, 'recall': 0.8783783783783784, 'f1-score': 0.8934707903780069, 'support': 148}, 'PER': {'precision': 0.9375, 'recall': 0.9202453987730062, 'f1-score': 0.9287925696594428, 'support': 163}, 'micro avg': {'precision': 0.8776824034334764, 'recall': 0.9316628701594533, 'f1-score': 0.903867403314917, 'support': 878}, 'macro avg': {'precision': 0.9016626439442726, 'recall': 0.9340434989704736, 'f1-score': 0.9164890128596201, 'support': 878}, 'weighted avg': {'precision': 0.8825485352999964, 'recall': 0.9316628701594533, 'f1-score': 0.9050173682107981, 'support': 878}} |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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