File size: 2,385 Bytes
b7b3ff2 | 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 | ---
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_378
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_378
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: 0.6314
- Accuracy: 0.8464
- 1-f1: 0.2469
- 1-recall: 0.9423
- 1-precision: 0.1420
- Balanced Acc: 0.8930
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:-----------:|:------------:|
| 0.192 | 1.0 | 19 | 0.6755 | 0.7883 | 0.1922 | 0.9423 | 0.1070 | 0.8632 |
| 0.2465 | 2.0 | 38 | 0.4063 | 0.8417 | 0.2414 | 0.9423 | 0.1384 | 0.8906 |
| 0.0752 | 3.0 | 57 | 0.7120 | 0.7996 | 0.2008 | 0.9423 | 0.1124 | 0.8690 |
| 0.1543 | 4.0 | 76 | 0.3070 | 0.9039 | 0.3345 | 0.9038 | 0.2052 | 0.9039 |
| 0.1197 | 5.0 | 95 | 0.7216 | 0.7924 | 0.1984 | 0.9615 | 0.1106 | 0.8746 |
| 0.0256 | 6.0 | 114 | 0.6314 | 0.8464 | 0.2469 | 0.9423 | 0.1420 | 0.8930 |
### Framework versions
- Transformers 4.46.3
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3
|