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---
base_model: klue/roberta-small
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: begging_classification
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. -->
# begging_classification
This model is a fine-tuned version of [klue/roberta-small](https://huggingface.co/klue/roberta-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0023
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log | 1.0 | 9 | 0.0986 | 1.0 | 0.92 | 0.9583 | 0.96 |
| No log | 2.0 | 18 | 0.0059 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 3.0 | 27 | 0.0032 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 4.0 | 36 | 0.0025 | 1.0 | 1.0 | 1.0 | 1.0 |
| No log | 5.0 | 45 | 0.0023 | 1.0 | 1.0 | 1.0 | 1.0 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1