File size: 3,148 Bytes
6b23be4 4af0db9 6b23be4 2093ddb 6b23be4 4af0db9 6b23be4 4af0db9 6b23be4 | 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 | ---
library_name: transformers
license: apache-2.0
base_model: google/rembert
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_404
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_404
This model is a fine-tuned version of [google/rembert](https://huggingface.co/google/rembert) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6947
- Accuracy: 0.9711
- 1-f1: 0.0
- 1-recall: 0.0
- 1-precision: 0.0
- Balanced Acc: 0.5
## 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: 16
- 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
- lr_scheduler_warmup_ratio: 0.06
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----:|:--------:|:-----------:|:------------:|
| 0.0097 | 1.0 | 494 | 1.0695 | 0.9711 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.004 | 2.0 | 988 | 1.0047 | 0.9711 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.8165 | 3.0 | 1482 | 0.7731 | 0.9711 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.9303 | 4.0 | 1976 | 0.8081 | 0.9711 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.8644 | 5.0 | 2470 | 0.7191 | 0.9711 | 0.0 | 0.0 | 0.0 | 0.5 |
| 1.0654 | 6.0 | 2964 | 0.7048 | 0.9711 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.0221 | 7.0 | 3458 | 0.6890 | 0.9711 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.0194 | 8.0 | 3952 | 0.7002 | 0.9711 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.0413 | 9.0 | 4446 | 0.6181 | 0.9711 | 0.0 | 0.0 | 0.0 | 0.5 |
| 1.3684 | 10.0 | 4940 | 0.6951 | 0.9711 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.7941 | 11.0 | 5434 | 0.7525 | 0.9711 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.672 | 12.0 | 5928 | 0.6746 | 0.9711 | 0.0 | 0.0 | 0.0 | 0.5 |
| 1.0709 | 13.0 | 6422 | 0.7167 | 0.9711 | 0.0 | 0.0 | 0.0 | 0.5 |
| 1.3019 | 14.0 | 6916 | 0.6947 | 0.9711 | 0.0 | 0.0 | 0.0 | 0.5 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|