File size: 2,796 Bytes
07e7e2d | 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 | ---
library_name: transformers
license: mit
base_model: AnonymousCS/populism_xlmr_large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: populism_classifier_bsample_209
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_209
This model is a fine-tuned version of [AnonymousCS/populism_xlmr_large](https://huggingface.co/AnonymousCS/populism_xlmr_large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6823
- Accuracy: 0.9523
- 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-06
- train_batch_size: 16
- eval_batch_size: 16
- 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: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | 1-f1 | 1-recall | 1-precision | Balanced Acc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.7204 | 1.0 | 333 | 0.6894 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6629 | 2.0 | 666 | 0.6907 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.7397 | 3.0 | 999 | 0.6969 | 0.0477 | 0.0911 | 1.0 | 0.0477 | 0.5 |
| 0.7098 | 4.0 | 1332 | 0.7190 | 0.0477 | 0.0911 | 1.0 | 0.0477 | 0.5 |
| 0.6755 | 5.0 | 1665 | 0.6673 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6648 | 6.0 | 1998 | 0.6775 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6746 | 7.0 | 2331 | 0.6761 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6863 | 8.0 | 2664 | 0.6947 | 0.0477 | 0.0911 | 1.0 | 0.0477 | 0.5 |
| 0.7181 | 9.0 | 2997 | 0.6894 | 0.9523 | 0.0 | 0.0 | 0.0 | 0.5 |
| 0.6689 | 10.0 | 3330 | 0.6823 | 0.9523 | 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
|