File size: 2,481 Bytes
c0b2b13 | 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 | ---
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_047
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. -->
# populism_classifier_bsample_047
This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5372
- Accuracy: 0.8091
- 1-f1: 0.4965
- 1-recall: 0.9211
- 1-precision: 0.3398
- Balanced Acc: 0.8587
## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.0578 | 1.0 | 6 | 0.6002 | 0.7554 | 0.4485 | 0.9737 | 0.2913 | 0.8521 |
| 0.0549 | 2.0 | 12 | 0.5505 | 0.7715 | 0.4654 | 0.9737 | 0.3058 | 0.8611 |
| 0.0779 | 3.0 | 18 | 0.7306 | 0.7016 | 0.4064 | 1.0 | 0.2550 | 0.8338 |
| 0.0312 | 4.0 | 24 | 0.5346 | 0.7823 | 0.4774 | 0.9737 | 0.3162 | 0.8671 |
| 0.0443 | 5.0 | 30 | 0.5190 | 0.7930 | 0.4901 | 0.9737 | 0.3274 | 0.8731 |
| 0.0212 | 6.0 | 36 | 0.8699 | 0.6640 | 0.3781 | 1.0 | 0.2331 | 0.8129 |
| 0.0305 | 7.0 | 42 | 0.5372 | 0.8091 | 0.4965 | 0.9211 | 0.3398 | 0.8587 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|