File size: 2,274 Bytes
f2fe438
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_english_bert_large_uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_384
  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_384

This model is a fine-tuned version of [AnonymousCS/populism_english_bert_large_uncased](https://huggingface.co/AnonymousCS/populism_english_bert_large_uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7028
- Accuracy: 0.7177
- 1-f1: 0.4870
- 1-recall: 0.9655
- 1-precision: 0.3256
- Balanced Acc: 0.8216

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.2064        | 1.0   | 5    | 1.0067          | 0.6746   | 0.4603 | 1.0      | 0.2990      | 0.8111       |
| 0.0468        | 2.0   | 10   | 0.5315          | 0.7799   | 0.54   | 0.9310   | 0.3803      | 0.8433       |
| 0.0149        | 3.0   | 15   | 0.4827          | 0.8325   | 0.6067 | 0.9310   | 0.45        | 0.8739       |
| 0.0147        | 4.0   | 20   | 0.6328          | 0.7225   | 0.4912 | 0.9655   | 0.3294      | 0.8244       |
| 0.0208        | 5.0   | 25   | 0.7028          | 0.7177   | 0.4870 | 0.9655   | 0.3256      | 0.8216       |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3