File size: 2,255 Bytes
39b1ae7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 |
---
license: mit
tags:
- generated_from_trainer
datasets:
- id_clickbait
metrics:
- accuracy
model-index:
- name: clickbait-classifier-20230408-001
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: id_clickbait
type: id_clickbait
config: annotated
split: train
args: annotated
metrics:
- name: Accuracy
type: accuracy
value: 0.7991666666666667
---
<!-- 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. -->
# clickbait-classifier-20230408-001
This model is a fine-tuned version of [indobenchmark/indobert-base-p1](https://huggingface.co./indobenchmark/indobert-base-p1) on the id_clickbait dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7645
- Accuracy: 0.7992
## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4419 | 1.0 | 675 | 0.3934 | 0.8275 |
| 0.3611 | 2.0 | 1350 | 0.4369 | 0.8367 |
| 0.2017 | 3.0 | 2025 | 0.5936 | 0.8258 |
| 0.1369 | 4.0 | 2700 | 0.9894 | 0.8058 |
| 0.0941 | 5.0 | 3375 | 1.1425 | 0.82 |
| 0.0428 | 6.0 | 4050 | 1.3502 | 0.7958 |
| 0.0236 | 7.0 | 4725 | 1.4706 | 0.8058 |
| 0.0197 | 8.0 | 5400 | 1.6508 | 0.7975 |
| 0.0041 | 9.0 | 6075 | 1.7922 | 0.7967 |
| 0.0037 | 10.0 | 6750 | 1.7645 | 0.7992 |
### Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
|