File size: 2,149 Bytes
26189fa | 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 | ---
library_name: transformers
license: apache-2.0
base_model: AnonymousCS/populism_multilingual_bert_cased_v2
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_134
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_134
This model is a fine-tuned version of [AnonymousCS/populism_multilingual_bert_cased_v2](https://huggingface.co/AnonymousCS/populism_multilingual_bert_cased_v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3076
- Accuracy: 0.9861
- 1-f1: 0.4681
- 1-recall: 0.3667
- 1-precision: 0.6471
- Balanced Acc: 0.6816
## 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: 128
- eval_batch_size: 128
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.3127 | 1.0 | 57 | 0.1542 | 0.9861 | 0.6154 | 0.6667 | 0.5714 | 0.8291 |
| 0.0751 | 2.0 | 114 | 0.1259 | 0.9705 | 0.4646 | 0.7667 | 0.3333 | 0.8703 |
| 0.0661 | 3.0 | 171 | 0.1418 | 0.9772 | 0.5060 | 0.7 | 0.3962 | 0.8409 |
| 0.0165 | 4.0 | 228 | 0.3076 | 0.9861 | 0.4681 | 0.3667 | 0.6471 | 0.6816 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|