File size: 2,514 Bytes
a9b9ac0 f980948 a9b9ac0 f980948 8888198 f980948 |
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 85 86 87 88 89 90 91 92 93 |
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: malaysia-news-classification-bert-malay
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. -->
# malaysia-news-classification-bert-malay
This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0311
- Accuracy: 0.7601
## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
## Label Mappings
This model can predict the following labels:
- `0`: Election
- `1`: Political Issue
- `2`: Corruption
- `3`: Democracy
- `4`: Economic Growth
- `5`: Economic Disparity
- `6`: Economic Subsidy
- `7`: Ethnic Discrimination
- `8`: Ethnic Relation
- `9`: Ethnic Culture
- `10`: Religious Issue
- `11`: Business and Finance
- `12`: Sport
- `13`: Food
- `14`: Entertainment
- `15`: Environmental Issue
- `16`: Domestic News
- `17`: World News
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 225 | 1.0295 | 0.7104 |
| No log | 2.0 | 450 | 0.9205 | 0.7409 |
| 1.1064 | 3.0 | 675 | 0.8432 | 0.7590 |
| 1.1064 | 4.0 | 900 | 0.8552 | 0.7695 |
| 0.5596 | 5.0 | 1125 | 0.8836 | 0.7612 |
| 0.5596 | 6.0 | 1350 | 0.9057 | 0.7665 |
| 0.3499 | 7.0 | 1575 | 0.9766 | 0.7590 |
| 0.3499 | 8.0 | 1800 | 0.9974 | 0.7640 |
| 0.2144 | 9.0 | 2025 | 1.0211 | 0.7612 |
| 0.2144 | 10.0 | 2250 | 1.0311 | 0.7601 |
### Framework versions
- Transformers 4.18.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.12.1
|